Back to Multiple platform build/check report for BioC 3.14 |
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This page was generated on 2022-04-13 12:05:40 -0400 (Wed, 13 Apr 2022).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4324 |
tokay2 | Windows Server 2012 R2 Standard | x64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4077 |
machv2 | macOS 10.14.6 Mojave | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4137 |
Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X |
To the developers/maintainers of the MungeSumstats package: - Please allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/MungeSumstats.git to reflect on this report. See How and When does the builder pull? When will my changes propagate? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
Package 1252/2083 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
MungeSumstats 1.2.4 (landing page) Alan Murphy
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) / x86_64 | OK | OK | OK | |||||||||
tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | |||||||||
machv2 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK | |||||||||
Package: MungeSumstats |
Version: 1.2.4 |
Command: /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD check --install=check:MungeSumstats.install-out.txt --library=/home/biocbuild/bbs-3.14-bioc/R/library --no-vignettes --timings MungeSumstats_1.2.4.tar.gz |
StartedAt: 2022-04-12 08:24:44 -0400 (Tue, 12 Apr 2022) |
EndedAt: 2022-04-12 08:42:36 -0400 (Tue, 12 Apr 2022) |
EllapsedTime: 1072.1 seconds |
RetCode: 0 |
Status: OK |
CheckDir: MungeSumstats.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD check --install=check:MungeSumstats.install-out.txt --library=/home/biocbuild/bbs-3.14-bioc/R/library --no-vignettes --timings MungeSumstats_1.2.4.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.14-bioc/meat/MungeSumstats.Rcheck’ * using R version 4.1.3 (2022-03-10) * using platform: x86_64-pc-linux-gnu (64-bit) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘MungeSumstats/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘MungeSumstats’ version ‘1.2.4’ * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘MungeSumstats’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking R files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... OK * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking contents of ‘data’ directory ... OK * checking data for non-ASCII characters ... OK * checking data for ASCII and uncompressed saves ... OK * checking R/sysdata.rda ... OK * checking files in ‘vignettes’ ... OK * checking examples ... OK Examples with CPU (user + system) or elapsed time > 5s user system elapsed get_genome_builds 59.326 5.522 64.882 format_sumstats 32.878 3.708 36.658 * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘testthat.R’ OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes in ‘inst/doc’ ... OK * checking running R code from vignettes ... SKIPPED * checking re-building of vignette outputs ... SKIPPED * checking PDF version of manual ... OK * DONE Status: OK
MungeSumstats.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD INSTALL MungeSumstats ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.14-bioc/R/library’ * installing *source* package ‘MungeSumstats’ ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (MungeSumstats)
MungeSumstats.Rcheck/tests/testthat.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up" Copyright (C) 2022 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(testthat) > library(MungeSumstats) > > test_check("MungeSumstats") Collecting metadata from Open GWAS. Filtering metadata by substring criteria. Found 3 GWAS datasets matching search criteria across: - 3 trait(s) - 1 population(s) - 2 category(ies) - 2 subcategory(ies) - 2 publication(s) - 2 consortia(ium) - 1 genome build(s) Collecting metadata from Open GWAS. Filtering metadata by substring criteria. Filtering metadata by sample/case/control/SNP size criteria. Excluding sample/case/control size with NAs. Found 3 GWAS datasets matching search criteria across: - 3 trait(s) - 1 population(s) - 2 category(ies) - 2 subcategory(ies) - 2 publication(s) - 2 consortia(ium) - 1 genome build(s) Collecting metadata from Open GWAS. Filtering metadata by substring criteria. Found 28 GWAS datasets matching search criteria across: - 26 trait(s) - 1 population(s) - 2 category(ies) - 2 subcategory(ies) - 3 publication(s) - 5 consortia(ium) - 1 genome build(s) Downloading VCF ==> /tmp/RtmpFPxtDO/ieu-a-298.vcf.gz Downloading with download.file. trying URL 'https://gwas.mrcieu.ac.uk/files/ieu-a-298/ieu-a-298.vcf.gz' Content type 'application/gzip' length 234480 bytes (228 KB) ================================================== downloaded 228 KB Downloading VCF index ==> https://gwas.mrcieu.ac.uk/files/ieu-a-298/ieu-a-298.vcf.gz.tbi Downloading with download.file. trying URL 'https://gwas.mrcieu.ac.uk/files/ieu-a-298/ieu-a-298.vcf.gz.tbi' Content type 'application/gzip' length 37803 bytes (36 KB) ================================================== downloaded 36 KB Processing 1 datasets from Open GWAS. ========== Processing dataset : a-fake-id ========== Downloading VCF ==> /tmp/RtmpFPxtDO/a-fake-id.vcf.gz Downloading with download.file. trying URL 'https://gwas.mrcieu.ac.uk/files/a-fake-id/a-fake-id.vcf.gz' Processing 1 datasets from Open GWAS. ========== Processing dataset : ieu-a-298 ========== Downloading VCF ==> /tmp/RtmpFPxtDO/ieu-a-298.vcf.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30162a372c9.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa301285b387a Standardising column headers. First line of summary statistics file: MarkerName CHR POS A0 A1 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30162a372c9.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30177f2900a.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa301285b387a Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30177f2900a.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30176a8ccf5.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa301247e50fa Standardising column headers. First line of summary statistics file: MarkerName CHR POS A2 A1 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for correct direction of A1 (reference) and A2 (alternative allele). Loading reference genome data. There are 47 SNPs where A1 doesn't match the reference genome. These will be flipped with their effect columns. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for bi-allelic SNPs. Warning: When method is an integer, must be >0. 67 SNPs (72%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30176a8ccf5.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 G A 0.63060 -0.017 0.003 2.359e-10 3: rs34305371 1 72733610 G A 0.91231 -0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3014c9ad2b4.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa301247e50fa Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Ensuring all SNPs are on the reference genome. Loading reference genome data. Checking for correct direction of A1 (reference) and A2 (alternative allele). There are 46 SNPs where A1 doesn't match the reference genome. These will be flipped with their effect columns. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for bi-allelic SNPs. Warning: When method is an integer, must be >0. 67 SNPs (72%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3014c9ad2b4.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 G A 0.63060 -0.017 0.003 2.359e-10 3: rs34305371 1 72733610 G A 0.91231 -0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30132cc27ed.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3016e4ede46 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for bi-allelic SNPs. Loading reference genome data. 1 SNPs are non-biallelic. These will be removed. Writing in tabular format ==> /tmp/RtmpFPxtDO/snp_bi_allelic.tsv.gz Warning: When method is an integer, must be >0. 46 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30132cc27ed.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3016e1ddae2.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3016e4ede46 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for bi-allelic SNPs. Loading reference genome data. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3016e1ddae2.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30117f0f36e.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014365da4a Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Ensuring parameters comply with LDSC format. Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. 1 SNP IDs are not correctly formatted. These will be corrected from the reference genome. Checking for merged allele column. Ensuring all SNPs are on the reference genome. Loading reference genome data. Checking for correct direction of A1 (reference) and A2 (alternative allele). There are 46 SNPs where A1 doesn't match the reference genome. These will be flipped with their effect columns. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for bi-allelic SNPs. Computing Z-score from P using formula: `sign(BETA)*sqrt(stats::qchisq(P,1,lower=FALSE)` Assigning N=1001 for all SNPs. 67 SNPs (72%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30117f0f36e.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P IMPUTATION_SNP 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 NA 2: rs11210860 1 43982527 G A 0.63060 -0.017 0.003 2.359e-10 NA 3: rs34305371 1 72733610 G A 0.91231 -0.035 0.005 3.762e-14 NA 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 NA flipped Z IMPUTATION_z_score N 1: NA 5.630777 TRUE 1001 2: TRUE -6.335939 TRUE 1001 3: TRUE -7.568968 TRUE 1001 4: NA -5.630488 TRUE 1001 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30112253e26.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013a8bfbb6 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N_CON N_CAS Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Ensuring all SNPs are on the reference genome. Loading reference genome data. Checking for correct direction of A1 (reference) and A2 (alternative allele). There are 46 SNPs where A1 doesn't match the reference genome. These will be flipped with their effect columns. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for bi-allelic SNPs. Computing effective sample size using the LDSC method: Neff = (N_CAS+N_CON) * (N_CAS/(N_CAS+N_CON)) / mean((N_CAS/(N_CAS+N_CON))[(N_CAS+N_CON)==max(N_CAS+N_CON)])) Computing sample size using the sum method: N = N_CAS + N_CON Computing effective sample size using the GIANT method: Neff = 2 / (1/N_CAS + 1/N_CON) Computing effective sample size using the METAL method: Neff = 4 / (1/N_CAS + 1/N_CON) 67 SNPs (72%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30112253e26.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P N_CON N_CAS 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 100 120 2: rs11210860 1 43982527 G A 0.63060 -0.017 0.003 2.359e-10 100 120 3: rs34305371 1 72733610 G A 0.91231 -0.035 0.005 3.762e-14 100 120 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 100 120 Neff_ldsc N Neff_giant Neff_metal 1: 220 220 109 218 2: 220 220 109 218 3: 220 220 109 218 4: 220 220 109 218 Returning path to saved data. Reading header. Tabular format detected. Reading header. Tabular format detected. Reading header. Tabular format detected. Reading header. Reading header. Tabular format detected. Importing tabular file: /home/biocbuild/bbs-3.14-bioc/R/library/MungeSumstats/extdata/eduAttainOkbay.txt Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Computing Z-score from P using formula: `sign(BETA)*sqrt(stats::qchisq(P,1,lower=FALSE)` ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3017c908eb2.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3012d65edbd Standardising column headers. First line of summary statistics file: MarkerName EAF Beta SE Pval CHR_BP_A2_A1 Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Column CHR_BP_A2_A1 has been separated into the columns CHR, BP, A2, A1 Standardising column headers. First line of summary statistics file: SNP FRQ BETA SE P CHR BP A2 A1 Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3017c908eb2.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3012b296e34.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3012d65edbd Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3012b296e34.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30129d4810a.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30143de5865 Standardising column headers. First line of summary statistics file: MarkerName EAF Beta SE Pval CHR_BP_A2_A1 CHR_BP_A2_A1_2 Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Warning: Multiple columns in the sumstats file seem to relate to Chromosome:Base Pair position:A2:A1. The column CHR_BP_A2_A1_2 will be kept whereas the column(s) CHR_BP_A2_A1 will be removed. If this is not the correct column to keep, please remove all incorrect columns from those listed here before running `format_sumstats()`. Column CHR_BP_A2_A1_2 has been separated into the columns CHR, BP, A2, A1 Standardising column headers. First line of summary statistics file: SNP FRQ BETA SE P CHR BP A2 A1 Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30129d4810a.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3014b424c03.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30143de5865 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3014b424c03.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3015aa0dba4.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3017c348210 Standardising column headers. First line of summary statistics file: MarkerName CHR POS EAF Beta SE Pval alleles allele Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Warning: Multiple columns in the sumstats file seem to relate to alleles A1>A2. The column ALLELES will be kept whereas the column(s) ALLELE will be removed. If this is not the correct column to keep, please remove all incorrect columns from those listed here before running `format_sumstats()`. Column ALLELES has been separated into the columns A1, A2 Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3015aa0dba4.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301432046b.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3017c348210 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301432046b.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30148224252.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3017a470ed5 Standardising column headers. First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval CHR_BP Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Column CHR_BP has been separated into the columns CHR, BP Standardising column headers. First line of summary statistics file: SNP A1 A2 FRQ BETA SE P CHR BP Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30148224252.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301bdb6f94.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3017a470ed5 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301bdb6f94.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30156f3f63a.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014e268f01 Standardising column headers. First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval CHR_BP CHR_BP_2 Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Warning: Multiple columns in the sumstats file seem to relate to Chromosome:Base Pair position. The column CHR_BP_2 will be kept whereas the column(s) CHR_BP will be removed. If this is not the correct column to keep, please remove all incorrect columns from those listed here before running `format_sumstats()`. Column CHR_BP_2 has been separated into the columns CHR, BP Standardising column headers. First line of summary statistics file: SNP A1 A2 FRQ BETA SE P CHR BP Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30156f3f63a.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30140d5e871.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014e268f01 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30140d5e871.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30159a1a455.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3016aea6f1e Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30159a1a455.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301f2cf22b.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3015fa759b8 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301f2cf22b.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30136bf474f.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013632b642 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30136bf474f.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3014acbfc07.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Saving output messages to: /tmp/RtmpFPxtDO/MungeSumstats_log_msg.txt Any runtime errors will be saved to: /tmp/RtmpFPxtDO/MungeSumstats_log_output.txt Messages will not be printed to terminal. Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3017ce1ad12.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30138d78a1 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3017ce1ad12.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30176f1ce3a.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014e569883 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 186 rows - 93 unique variants - 140 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. 93 RSIDs are duplicated in the sumstats file. These duplicates will be removed Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30176f1ce3a.tsv.gz Summary statistics report: - 93 rows (50% of original 186 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301569927f2.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014e569883 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301569927f2.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3015ba504dd.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014e569883 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 94 rows - 94 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. 1 base-pair positions are duplicated in the sumstats file. These duplicates will be removed. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3015ba504dd.tsv.gz Summary statistics report: - 93 rows (98.9% of original 94 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3017e606bcd.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013b7055f2 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Filtering effect columns, ensuring none equal 0. 5 SNPs have effect values = 0 and will be removed Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 44 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3017e606bcd.tsv.gz Summary statistics report: - 88 rows (94.6% of original 93 rows) - 88 unique variants - 65 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30123b68ed7.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014113fa20 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval FRQ Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs based on FRQ. 38 SNPs are below the FRQ threshold of 0.9 and will be removed. Writing in tabular format ==> /tmp/RtmpFPxtDO/frq_filter.tsv.gz Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 55 SNPs (100%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30123b68ed7.tsv.gz Summary statistics report: - 55 rows (59.1% of original 93 rows) - 55 unique variants - 41 genome-wide significant variants (P<5e-8) - 16 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 EAF BETA SE P FRQ 1: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 1.863269 2: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 1.169733 3: rs1008078 1 91189731 T C 0.37310 -0.016 0.003 6.005e-10 1.401423 4: rs61787263 1 98618714 T C 0.76120 0.016 0.003 5.391e-08 1.873332 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301769178c5.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014113fa20 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval FRQ Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs based on FRQ. 38 SNPs are below the FRQ threshold of 0.9 and will be removed. Writing in tabular format ==> /tmp/RtmpFPxtDO/frq_filter.tsv.gz Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 55 SNPs (100%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=FALSE, the FRQ column will be renamed MAJOR_ALLELE_FRQ to differentiate the values from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301769178c5.tsv.gz Summary statistics report: - 55 rows (59.1% of original 93 rows) - 55 unique variants - 41 genome-wide significant variants (P<5e-8) - 16 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 EAF BETA SE P 1: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 2: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 3: rs1008078 1 91189731 T C 0.37310 -0.016 0.003 6.005e-10 4: rs61787263 1 98618714 T C 0.76120 0.016 0.003 5.391e-08 MAJOR_ALLELE_FRQ 1: 1.863269 2: 1.169733 3: 1.401423 4: 1.873332 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301b3e99f9.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30170b7cf67 Standardising column headers. First line of summary statistics file: SNP CHR BP A1 A2 FRQ BETA SE P Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301b3e99f9.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30114908cde.tsv Converting full summary stats file to tabix format for fast querying... Reading header. Ensuring file is bgzipped. Tabix-indexing file. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301633d1b90.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3016c02a20 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval INFO Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs based on INFO score. 38 SNPs are below the INFO threshold of 0.9 and will be removed. Writing in tabular format ==> /tmp/RtmpFPxtDO/info_filter.tsv.gz Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 28 SNPs (50.9%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301633d1b90.tsv.gz Summary statistics report: - 55 rows (59.1% of original 93 rows) - 55 unique variants - 41 genome-wide significant variants (P<5e-8) - 16 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P INFO 1: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 1.863269 2: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 1.169733 3: rs1008078 1 91189731 T C 0.37310 -0.016 0.003 6.005e-10 1.401423 4: rs61787263 1 98618714 T C 0.76120 0.016 0.003 5.391e-08 1.873332 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30125171430.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa301686d3650 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30125171430.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3016a81a586.tsv.gz Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3016a81a586.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3013b783571.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30147074787 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Ensuring all SNPs are on the reference genome. Loading reference genome data. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Performing data liftover from GRCh37 to GRCh38. Using existing chain file. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3013b783571.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8430543 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43516856 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72267927 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72296486 T C 0.23690 -0.017 0.003 1.797e-08 IMPUTATION_gen_build 1: TRUE 2: TRUE 3: TRUE 4: TRUE Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30137f57574.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013b783571.tsv.gz Standardising column headers. First line of summary statistics file: SNP CHR BP A1 A2 FRQ BETA SE P IMPUTATION_gen_build Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Ensuring all SNPs are on the reference genome. Loading reference genome data. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Performing data liftover from GRCh38 to GRCh37. Using existing chain file. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30137f57574.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 IMPUTATION_GEN_BUILD IMPUTATION_gen_build 1: TRUE TRUE 2: TRUE TRUE 3: TRUE TRUE 4: TRUE TRUE Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30150aa093e.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30147074787 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Ensuring all SNPs are on the reference genome. Loading reference genome data. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30150aa093e.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30176a14113.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3012d1441e5 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. WARNING: 1 rows in sumstats file are missing data and will be removed. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 46 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30176a14113.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs12646808 4 3249828 T C 0.64180 0.016 0.003 4.002e-08 2: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 3: rs117468730 16 10205467 A G 0.02425 -0.049 0.009 1.242e-07 4: rs76076331 2 10977585 T C 0.09328 0.020 0.004 3.632e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30116c8bf86.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3012d1441e5 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30116c8bf86.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs12646808 4 3249828 T C 0.64180 0.016 0.003 4.002e-08 2: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 3: rs117468730 16 10205467 A G 0.02425 -0.049 0.009 1.242e-07 4: rs76076331 2 10977585 T C 0.09328 0.020 0.004 3.632e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30189a3908.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014b80cad8 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. 1 SNPs found with multiple RSIDs on one row, the first will be taken. If you would rather remove these SNPs set `remove_multi_rs_snp=TRUE`. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30189a3908.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 convert_multi_rs_SNP 1: NA 2: NA 3: NA 4: NA Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3011717ba0b.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014b80cad8 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3011717ba0b.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30124131299.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa301f24b17d Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 92 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Writing in tabular format ==> /tmp/RtmpFPxtDO/snp_multi_rs_one_row.tsv.gz 1 SNPs found with multiple RSIDs on one row, these will be removed. If you would rather take the first RS ID set `remove_multi_rs_snp`=FALSE Checking SNP RSIDs. 1 SNP IDs are not correctly formatted. These will be corrected from the reference genome. Writing in tabular format ==> /tmp/RtmpFPxtDO/snp_not_found_from_chr_bp.tsv.gz Checking for merged allele column. Ensuring all SNPs are on the reference genome. Loading reference genome data. Checking for correct direction of A1 (reference) and A2 (alternative allele). There are 43 SNPs where A1 doesn't match the reference genome. These will be flipped with their effect columns. Checking for missing data. WARNING: 1 rows in sumstats file are missing data and will be removed. Writing in tabular format ==> /tmp/RtmpFPxtDO/missing_data.tsv.gz Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. 1 RSIDs are duplicated in the sumstats file. These duplicates will be removed Writing in tabular format ==> /tmp/RtmpFPxtDO/dup_snp_id.tsv.gz Checking for SNPs with duplicated base-pair positions. 1 base-pair positions are duplicated in the sumstats file. These duplicates will be removed. Writing in tabular format ==> /tmp/RtmpFPxtDO/dup_base_pair_position.tsv.gz Filtering SNPs, ensuring SE>0. 1 SNPs have SE values <= 0 and will be removed Writing in tabular format ==> /tmp/RtmpFPxtDO/se_neg.tsv.gz Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for strand ambiguous SNPs. 8 SNPs are strand-ambiguous alleles including 4 A/T and 4 C/G ambiguous SNPs. These will be removed Writing in tabular format ==> /tmp/RtmpFPxtDO/snp_strand_ambiguous.tsv.gz Checking for bi-allelic SNPs. Warning: When method is an integer, must be >0. 54 SNPs (68.4%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30124131299.tsv.gz Summary statistics report: - 79 rows (84.9% of original 93 rows) - 79 unique variants - 57 genome-wide significant variants (P<5e-8) - 18 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P IMPUTATION_SNP 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 NA 2: rs34305371 1 72733610 G A 0.91231 -0.035 0.005 3.762e-14 NA 3: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 NA 4: rs1008078 1 91189731 C T 0.62690 0.016 0.003 6.005e-10 NA flipped 1: NA 2: TRUE 3: NA 4: TRUE Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301f65c84f.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014d911217 Standardising column headers. First line of summary statistics file: chromosome rs_id markername position_hg18 Effect_allele Other_allele EAF_HapMapCEU N_SMK Effect_SMK StdErr_SMK P_value_SMK N_NONSMK Effect_NonSMK StdErr_NonSMK P_value_NonSMK Summary statistics report: - 5 rows - 5 unique variants - 1 chromosomes Checking for multi-GWAS. WARNING: Multiple traits found in sumstats file only one of which can be analysed: SMK, NONSMK Standardising column headers. First line of summary statistics file: CHR SNP MARKERNAME POSITION_HG18 A2 A1 EAF_HAPMAPCEU N EFFECT STDERR P_VALUE N_NONSMK EFFECT_NONSMK STDERR_NONSMK P_VALUE_NONSMK Checking for multiple RSIDs on one row. Checking SNP RSIDs. 1 SNP IDs are not correctly formatted and will be removed. Checking for merged allele column. Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Column MARKERNAME has been separated into the columns CHR, BP Standardising column headers. First line of summary statistics file: CHR SNP POSITION_HG18 A2 A1 EAF_HAPMAPCEU N BETA STDERR P N_NONSMK EFFECT_NONSMK STDERR_NONSMK P_VALUE_NONSMK BP Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Ensuring that the N column is all integers. The sumstats N column is not all integers, this could effect downstream analysis. These will be converted to integers. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Ensuring all SNPs have N<5 std dev above mean. Making X/Y CHR uppercase. N already exists within sumstats_dt. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301f65c84f.tsv.gz Summary statistics report: - 4 rows (80% of original 5 rows) - 4 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 POSITION_HG18 EAF_HAPMAPCEU N BETA 1: rs1000085 chr1 66630503 G C 66630503 0.1667 38761 0.0053 2: rs1000075 chr1 94939420 C T 94939420 0.3583 38959 -0.0013 3: rs1000073 chr1 155522020 G A 155522020 0.3136 36335 0.0046 4: rs1000050 chr1 161003087 C T 161003087 0.9000 36257 0.0001 STDERR P N_NONSMK EFFECT_NONSMK STDERR_NONSMK P_VALUE_NONSMK 1: 0.0095 0.5746 147259 -0.0034 0.0052 0.5157 2: 0.0082 0.8687 147567 -0.0043 0.0044 0.3259 3: 0.0083 0.5812 126780 0.0038 0.0045 0.3979 4: 0.0109 0.9931 127514 0.0058 0.0059 0.3307 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3015cfe0eb.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3015615afde Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N N_fixed Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Ensuring that the N column is all integers. The sumstats N column is not all integers, this could effect downstream analysis. These will be converted to integers. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. N already exists within sumstats_dt. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3015cfe0eb.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P N N_FIXED 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 5 5 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 1 1 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 1 1 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 7 7 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301285b9648.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3018ee1b1e Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. The sumstats N column is not all integers, this could effect downstream analysis.These will NOT be converted to integers. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 1 SNPs have N values 5 standard deviations above the mean and will be removed Writing in tabular format ==> /tmp/RtmpFPxtDO/n_large.tsv.gz Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. N already exists within sumstats_dt. 47 SNPs (51.1%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301285b9648.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P N 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 3 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 5 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 3 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 3 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3011ba32204.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3018ee1b1e Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. The sumstats N column is not all integers, this could effect downstream analysis.These will NOT be converted to integers. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 1 SNPs have N values 5 standard deviations above the mean and will be removed Writing in tabular format ==> /tmp/RtmpFPxtDO/n_large.tsv.gz Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. N already exists within sumstats_dt. 47 SNPs (51.1%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3011ba32204.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P N 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 3 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 5 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 3 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 3 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301161ae77.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3018ee1b1e Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. The sumstats N column is not all integers, this could effect downstream analysis.These will NOT be converted to integers. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 1 SNPs have N values 5 standard deviations above the mean and will be removed Writing in tabular format ==> /tmp/RtmpFPxtDO/n_large.tsv.gz Removing rows where is.na(N) 0 SNPs have N values that are NA and will be removed. Writing in tabular format ==> /tmp/RtmpFPxtDO/n_null.tsv.gz Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. N already exists within sumstats_dt. 47 SNPs (51.1%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301161ae77.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P N 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 3 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 5 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 3 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 3 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301270407ac.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30138b63b7b Standardising column headers. First line of summary statistics file: MarkerName CHR POS EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. WARNING: No A2 column found in the data, multi-allelic can't not be accurately chosen (as any of the choices could be valid). bi_allelic_filter has been forced to TRUE. Loading reference genome data. There is no A1 or A2 allele information column found within the data. It must be inferred from other column information. Deriving both A1 and A2 from reference genome WARNING: Inferring the alternative allele (A2) from the reference genome. In some instances, there are more than one alternative allele. Arbitrarily, only the first will be kept. See column `alt_alleles` in your returned sumstats file for all alternative alleles. Writing in tabular format ==> /tmp/RtmpFPxtDO/alleles_not_found_from_snp.tsv.gz Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for bi-allelic SNPs. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301270407ac.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P alt_alleles 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 C 2: rs11210860 1 43982527 G A 0.36940 0.017 0.003 2.359e-10 A 3: rs34305371 1 72733610 G A 0.08769 0.035 0.005 3.762e-14 A 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 C IMPUTATION_A1 IMPUTATION_A2 1: TRUE TRUE 2: TRUE TRUE 3: TRUE TRUE 4: TRUE TRUE Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3011d79e8b7.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30138b63b7b Standardising column headers. First line of summary statistics file: MarkerName CHR POS A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Loading reference genome data. There is no A1 or A2 allele information column found within the data. It must be inferred from other column information. One of A1/A2 are missing, allele flipping will be tested Deriving A1 from reference genome Writing in tabular format ==> /tmp/RtmpFPxtDO/alleles_not_found_from_snp.tsv.gz Checking for correct direction of A1 (reference) and A2 (alternative allele). There are 46 SNPs where A1 doesn't match the reference genome. These will be flipped with their effect columns. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3011d79e8b7.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P IMPUTATION_A1 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 TRUE 2: rs11210860 1 43982527 G G 0.36940 -0.017 0.003 2.359e-10 TRUE 3: rs34305371 1 72733610 G G 0.08769 -0.035 0.005 3.762e-14 TRUE 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 TRUE flipped 1: NA 2: TRUE 3: TRUE 4: NA Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30165a0e36b.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30138b63b7b Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. WARNING: No A2 column found in the data, multi-allelic can't not be accurately chosen (as any of the choices could be valid). bi_allelic_filter has been forced to TRUE. Loading reference genome data. There is no A1 or A2 allele information column found within the data. It must be inferred from other column information. One of A1/A2 are missing, allele flipping will be tested Deriving A2 from reference genome WARNING: Inferring the alternative allele (A2) from the reference genome. In some instances, there are more than one alternative allele. Arbitrarily, only the first will be kept. See column `alt_alleles` in your returned sumstats file for all alternative alleles. Writing in tabular format ==> /tmp/RtmpFPxtDO/alleles_not_found_from_snp.tsv.gz Checking for correct direction of A1 (reference) and A2 (alternative allele). Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for bi-allelic SNPs. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30165a0e36b.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P alt_alleles 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 C 2: rs11210860 1 43982527 A A 0.36940 0.017 0.003 2.359e-10 A 3: rs34305371 1 72733610 A A 0.08769 0.035 0.005 3.762e-14 A 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 C IMPUTATION_A2 1: TRUE 2: TRUE 3: TRUE 4: TRUE Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3012ade06bd.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30138b63b7b Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for correct direction of A1 (reference) and A2 (alternative allele). Loading reference genome data. There are 46 SNPs where A1 doesn't match the reference genome. These will be flipped with their effect columns. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3012ade06bd.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 G A 0.36940 -0.017 0.003 2.359e-10 3: rs34305371 1 72733610 G A 0.08769 -0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3012320c5b9.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa301656408e4 Standardising column headers. First line of summary statistics file: MarkerName POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Standardising column headers. First line of summary statistics file: SNP BP A1 A2 FRQ BETA SE P Loading reference genome data. There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3012320c5b9.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3015f89dd6f.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3012e1b28cb Standardising column headers. First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Standardising column headers. First line of summary statistics file: SNP A1 A2 FRQ BETA SE P Loading reference genome data. There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information. Writing in tabular format ==> /tmp/RtmpFPxtDO/chr_bp_not_found_from_snp.tsv.gz Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3015f89dd6f.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3015904d6c5.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30178e30a99 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. 1 SNP IDs are not correctly formatted. These will be corrected from the reference genome. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3015904d6c5.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3014c657ea2.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30178e30a99 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3014c657ea2.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3012f51dd33.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013d2ad6af Standardising column headers. First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. 1 SNP IDs appear to be made up of chr:bp, these will be replaced by their SNP ID from the reference genome 1 SNP IDs are not correctly formatted and will be removed. Checking for merged allele column. Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Standardising column headers. First line of summary statistics file: SNP A1 A2 FRQ BETA SE P Loading reference genome data. There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 46 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3012f51dd33.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301247a4260.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3016ec82b63 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. 1 SNP IDs are not correctly formatted. These will be corrected from the reference genome. 1 SNP IDs appear to be made up of chr:bp, these will be replaced by their SNP ID from the reference genome Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301247a4260.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3012c17a51b.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa301ab59d56 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30137b9d7e0.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013d2ad6af Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30137b9d7e0.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3017326ced2.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013e308a6e Standardising column headers. First line of summary statistics file: CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking for merged allele column. There is no SNP column found within the data. It must be inferred from other column information. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3017326ced2.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3011dfc2d36.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013d04d484 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Ensuring all SNPs are on the reference genome. Loading reference genome data. 1 SNPs are not on the reference genome. These will be corrected from the reference genome. Writing in tabular format ==> /tmp/RtmpFPxtDO/snp_not_found_from_chr_bp.tsv.gz Loading reference genome data. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3011dfc2d36.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3016a6ada09.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013d04d484 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Ensuring all SNPs are on the reference genome. Loading reference genome data. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3016a6ada09.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. Inferring genome build of 1 sumstats file(s). ss1 Inferring genome build. Reading in only the first 50 rows of sumstats. Reading header. Tabular format detected. Importing tabular file: /home/biocbuild/bbs-3.14-bioc/R/library/MungeSumstats/extdata/eduAttainOkbay.txt Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Loading reference genome data. Loading reference genome data. Inferred genome build: GRCH37 Time difference of 45.14929 secs GRCH37: 1 file(s) ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301448ceb90.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3016a56f583 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 23 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. 3 SNPs are on chromosomes X, Y, MT and will be removed Writing in tabular format ==> /tmp/RtmpFPxtDO/chr_excl.tsv.gz Warning: When method is an integer, must be >0. 45 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301448ceb90.tsv.gz Summary statistics report: - 90 rows (96.8% of original 93 rows) - 90 unique variants - 67 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3017b7f455b.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3016a56f583 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3017b7f455b.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3016859d25d Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013aecf8c1 Converting summary statistics to Genomic Ranges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpFPxtDO/fileaa3012d2a011d.vcf.gz Reading header. Importing VCF file: /tmp/RtmpFPxtDO/fileaa3012d2a011d.vcf.gz Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT GWAS Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'GWAS' data column. 1 empty column(s) detected. Formatting INFO column. NOTE: All INFO scores are empty. Replacing all with 1. Standardising column headers. First line of summary statistics file: CHR BP SNP A1 A2 INFO FRQ BETA SE P 0 empty column(s) detected. Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT EBI-a-GCST005647 Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'EBI-A-GCST005647' data column. 0 empty column(s) detected. VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column. Formatting INFO column. INFO column is actually AF, it will be converted. Standardising column headers. First line of summary statistics file: CHR BP SNP A1 A2 INFO ES SE LP AF ID P Converting summary statistics to Genomic Ranges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpFPxtDO/fileaa30143520781.vcf.gz Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT GWAS Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'GWAS' data column. 0 empty column(s) detected. VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column. Formatting INFO column. Standardising column headers. First line of summary statistics file: CHR BP SNP A1 A2 INFO BETA SE LP FRQ ID P ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30123e639f7.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Standardising column headers. First line of summary statistics file: SNP P FRQ BETA CHR BP Summary statistics report: - 5 rows - 5 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. 5 SNP IDs contain other information in the same column. These will be separated. Checking for merged allele column. Column SNP_INFO has been separated into the columns A1, A2 Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 3 SNPs (60%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30123e639f7.tsv.gz Summary statistics report: - 5 rows (100% of original 5 rows) - 5 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 P FRQ BETA 1: rs140052487 1 54353 C A 0.037219838 0.3000548 0.8797957 2: rs558796213 1 54564 G T 0.004382482 0.5848666 0.7068747 3: rs561234294 1 54591 A G 0.070968402 0.3334671 0.7319726 4: rs2462492 1 54676 C T 0.065769040 0.6220120 0.9316344 Returning data directly. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30145468557.tsv.gz Log data to be saved to ==> /tmp/RtmpFPxtDO Standardising column headers. First line of summary statistics file: SNP P FRQ BETA CHR BP A1 A2 Summary statistics report: - 5 rows - 5 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 3 SNPs (60%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30145468557.tsv.gz Summary statistics report: - 5 rows (100% of original 5 rows) - 5 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 P FRQ BETA 1: rs140052487 1 54353 C A 0.037219838 0.3000548 0.8797957 2: rs558796213 1 54564 G T 0.004382482 0.5848666 0.7068747 3: rs561234294 1 54591 A G 0.070968402 0.3334671 0.7319726 4: rs2462492 1 54676 C T 0.065769040 0.6220120 0.9316344 Returning data directly. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3012fb15f60.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3012c83051d Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3013e967bca.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa301528be164 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. There are existing p-values as low as 5e-324 which LDSC/MAGMA may not be able to handle. These will be converted to 0. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3013e967bca.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3011424a49b.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa301528be164 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3011424a49b.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301564e12e9.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3015e77029e Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301564e12e9.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3013ef9dcbc.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3012aee1d96 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3013ef9dcbc.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30167b121.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3011955f433 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. 5 SNPs have SE values <= 0 and will be removed Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 44 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30167b121.tsv.gz Summary statistics report: - 88 rows (94.6% of original 93 rows) - 88 unique variants - 65 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3014ce454b5.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3011bf1d1a0 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 85 rows - 85 unique variants - 63 genome-wide significant variants (P<5e-8) - 19 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for strand ambiguous SNPs. Warning: When method is an integer, must be >0. 43 SNPs (50.6%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3014ce454b5.tsv.gz Summary statistics report: - 85 rows (100% of original 85 rows) - 85 unique variants - 63 genome-wide significant variants (P<5e-8) - 19 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3016108f950.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3011bf1d1a0 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for strand ambiguous SNPs. 8 SNPs are strand-ambiguous alleles including 4 A/T and 4 C/G ambiguous SNPs. These will be removed Warning: When method is an integer, must be >0. 43 SNPs (50.6%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3016108f950.tsv.gz Summary statistics report: - 85 rows (91.4% of original 93 rows) - 85 unique variants - 63 genome-wide significant variants (P<5e-8) - 19 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3015140d651.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30140949591.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013f7ffbef Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30140949591.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 EAF BETA SE P 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning data directly. Converting summary statistics to Genomic Ranges. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30169d331cf.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3014645980f.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3016caa4acd.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30125775037.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3013485bd27.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3012d78eb48.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3011782ec4a.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30111073450.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3017dcf46d4.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30130d8e07d.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301116ee571.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301f755a08.tsv.gz Reading header. Importing VCF file: /tmp/RtmpFPxtDO/fileaa3011ab231f3.vcf Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT EBI-a-GCST005647 Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'EBI-A-GCST005647' data column. 0 empty column(s) detected. VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column. Formatting INFO column. INFO column is actually AF, it will be converted. Standardising column headers. First line of summary statistics file: CHR BP SNP A1 A2 INFO ES SE LP AF ID P Summary statistics report: - 101 rows - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. 2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed. Filtering SNPs based on INFO score. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301f755a08.tsv.gz Summary statistics report: - 99 rows (98% of original 101 rows) - 99 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 INFO BETA SE LP FRQ 1: rs58108140 1 10583 G A 0.1589 0.0312 0.0393 0.369267 0.1589 2: rs806731 1 30923 G T 0.7843 -0.0114 0.0353 0.126854 0.7843 3: rs116400033 1 51479 T A 0.1829 0.0711 0.0370 1.262410 0.1829 4: rs146477069 1 54421 A G 0.0352 -0.0240 0.0830 0.112102 0.0352 ID P 1: rs58108140 0.42730011 2: rs806731 0.74669974 3: rs116400033 0.05464998 4: rs146477069 0.77249913 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3011dc332f4.tsv.gz Reading header. Importing VCF file: /tmp/RtmpFPxtDO/fileaa30164182230.vcf Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT EBI-a-GCST005647 Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'EBI-A-GCST005647' data column. 0 empty column(s) detected. VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column. Formatting INFO column. INFO column is actually AF, it will be converted. Standardising column headers. First line of summary statistics file: CHR BP SNP A1 A2 INFO ES SE LP AF ID P Summary statistics report: - 101 rows - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for correct direction of A1 (reference) and A2 (alternative allele). Loading reference genome data. There are 1 SNPs where A1 doesn't match the reference genome. These will be flipped with their effect columns. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. 2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed. Filtering SNPs based on INFO score. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Checking for bi-allelic SNPs. Warning: When method is an integer, must be >0. 2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3011dc332f4.tsv.gz Summary statistics report: - 99 rows (98% of original 101 rows) - 99 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 INFO BETA SE LP FRQ 1: rs58108140 1 10583 G A 0.1589 0.0312 0.0393 0.369267 0.1589 2: rs806731 1 30923 G T 0.7843 -0.0114 0.0353 0.126854 0.7843 3: rs116400033 1 51479 T A 0.1829 0.0711 0.0370 1.262410 0.1829 4: rs146477069 1 54421 A G 0.0352 -0.0240 0.0830 0.112102 0.0352 ID P 1: rs58108140 0.42730011 2: rs806731 0.74669974 3: rs116400033 0.05464998 4: rs146477069 0.77249913 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3019f3d0.tsv.gz Reading header. Importing VCF file: /home/biocbuild/bbs-3.14-bioc/R/library/MungeSumstats/extdata/ALSvcf.vcf Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT EBI-a-GCST005647 Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'EBI-A-GCST005647' data column. 0 empty column(s) detected. VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column. Formatting INFO column. INFO column is actually AF, it will be converted. Standardising column headers. First line of summary statistics file: CHR BP SNP A1 A2 INFO ES SE LP AF ID P Summary statistics report: - 101 rows - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. 2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed. Filtering SNPs based on INFO score. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3019f3d0.tsv.gz Summary statistics report: - 99 rows (98% of original 101 rows) - 99 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 INFO BETA SE LP FRQ 1: rs58108140 1 10583 G A 0.1589 0.0312 0.0393 0.369267 0.1589 2: rs806731 1 30923 G T 0.7843 -0.0114 0.0353 0.126854 0.7843 3: rs116400033 1 51479 T A 0.1829 0.0711 0.0370 1.262410 0.1829 4: rs146477069 1 54421 A G 0.0352 -0.0240 0.0830 0.112102 0.0352 ID P 1: rs58108140 0.42730011 2: rs806731 0.74669974 3: rs116400033 0.05464998 4: rs146477069 0.77249913 Returning data directly. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3015d6238fd.tsv.gz Reading header. Importing VCF file: /home/biocbuild/bbs-3.14-bioc/R/library/MungeSumstats/extdata/ALSvcf.vcf Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT EBI-a-GCST005647 Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'EBI-A-GCST005647' data column. 0 empty column(s) detected. VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column. Formatting INFO column. INFO column is actually AF, it will be converted. Standardising column headers. First line of summary statistics file: CHR BP SNP A1 A2 INFO ES SE LP AF ID P Summary statistics report: - 101 rows - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. 2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed. Filtering SNPs based on INFO score. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3015d6238fd.tsv.gz Summary statistics report: - 99 rows (98% of original 101 rows) - 99 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 INFO BETA SE LP FRQ 1: rs58108140 1 10583 G A 0.1589 0.0312 0.0393 0.369267 0.1589 2: rs806731 1 30923 G T 0.7843 -0.0114 0.0353 0.126854 0.7843 3: rs116400033 1 51479 T A 0.1829 0.0711 0.0370 1.262410 0.1829 4: rs146477069 1 54421 A G 0.0352 -0.0240 0.0830 0.112102 0.0352 ID P 1: rs58108140 0.42730011 2: rs806731 0.74669974 3: rs116400033 0.05464998 4: rs146477069 0.77249913 Returning data directly. Converting summary statistics to Genomic Ranges. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3014bb080fa.tsv.gz Reading header. Importing VCF file: /home/biocbuild/bbs-3.14-bioc/R/library/MungeSumstats/extdata/ALSvcf.vcf Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT EBI-a-GCST005647 Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'EBI-A-GCST005647' data column. 0 empty column(s) detected. VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column. Formatting INFO column. INFO column is actually AF, it will be converted. Standardising column headers. First line of summary statistics file: CHR BP SNP A1 A2 INFO ES SE LP AF ID P Summary statistics report: - 101 rows - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. 2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed. Filtering SNPs based on INFO score. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3014bb080fa.tsv.gz Summary statistics report: - 99 rows (98% of original 101 rows) - 99 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 INFO BETA SE LP FRQ 1: rs58108140 1 10583 G A 0.1589 0.0312 0.0393 0.369267 0.1589 2: rs806731 1 30923 G T 0.7843 -0.0114 0.0353 0.126854 0.7843 3: rs116400033 1 51479 T A 0.1829 0.0711 0.0370 1.262410 0.1829 4: rs146477069 1 54421 A G 0.0352 -0.0240 0.0830 0.112102 0.0352 ID P 1: rs58108140 0.42730011 2: rs806731 0.74669974 3: rs116400033 0.05464998 4: rs146477069 0.77249913 Returning data directly. Converting summary statistics to Genomic Ranges. Converting summary statistics to VRanges. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30178b7434a.tsv.gz Reading header. Importing VCF file: /home/biocbuild/bbs-3.14-bioc/R/library/MungeSumstats/extdata/ALSvcf.vcf Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT EBI-a-GCST005647 Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'EBI-A-GCST005647' data column. 0 empty column(s) detected. VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column. Formatting INFO column. INFO column is actually AF, it will be converted. Standardising column headers. First line of summary statistics file: CHR BP SNP A1 A2 INFO ES SE LP AF ID P Summary statistics report: - 101 rows - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Inferring genome build. Loading reference genome data. Loading reference genome data. Inferred genome build: GRCH37 Checking SNP RSIDs. Checking for merged allele column. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. 2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed. Filtering SNPs based on INFO score. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Warning: When method is an integer, must be >0. 2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30178b7434a.tsv.gz Summary statistics report: - 99 rows (98% of original 101 rows) - 99 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 INFO BETA SE LP FRQ 1: rs58108140 1 10583 G A 0.1589 0.0312 0.0393 0.369267 0.1589 2: rs806731 1 30923 G T 0.7843 -0.0114 0.0353 0.126854 0.7843 3: rs116400033 1 51479 T A 0.1829 0.0711 0.0370 1.262410 0.1829 4: rs146477069 1 54421 A G 0.0352 -0.0240 0.0830 0.112102 0.0352 ID P 1: rs58108140 0.42730011 2: rs806731 0.74669974 3: rs116400033 0.05464998 4: rs146477069 0.77249913 Returning data directly. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3012995d2b6.tsv.gz Reading header. Importing VCF file: /home/biocbuild/bbs-3.14-bioc/R/library/MungeSumstats/extdata/ALSvcf.vcf Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT EBI-a-GCST005647 Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'EBI-A-GCST005647' data column. 0 empty column(s) detected. VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column. Formatting INFO column. INFO column is actually AF, it will be converted. Standardising column headers. First line of summary statistics file: CHR BP SNP A1 A2 INFO ES SE LP AF ID P Ensuring parameters comply with LDSC format. Setting `compute_z=TRUE` to comply with LDSC format. Summary statistics report: - 101 rows - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking for correct direction of A1 (reference) and A2 (alternative allele). Loading reference genome data. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. 2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed. Filtering SNPs based on INFO score. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Removing 'chr' prefix from CHR. Making X/Y CHR uppercase. Computing Z-score from P using formula: `sign(BETA)*sqrt(stats::qchisq(P,1,lower=FALSE)` Assigning N=1001 for all SNPs. 2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates. Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3012995d2b6.tsv.gz Summary statistics report: - 99 rows (98% of original 101 rows) - 99 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 INFO BETA SE LP FRQ 1: rs58108140 1 10583 G A 0.1589 0.0312 0.0393 0.369267 0.1589 2: rs806731 1 30923 G T 0.7843 -0.0114 0.0353 0.126854 0.7843 3: rs116400033 1 51479 T A 0.1829 0.0711 0.0370 1.262410 0.1829 4: rs146477069 1 54421 A G 0.0352 -0.0240 0.0830 0.112102 0.0352 ID P Z N 1: rs58108140 0.42730011 0.7938202 1001 2: rs806731 0.74669974 -0.3229941 1001 3: rs116400033 0.05464998 1.9216487 1001 4: rs146477069 0.77249913 -0.2891075 1001 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3011ae8eb63.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30175e4e682 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Summary statistics report: - 93 rows - 93 unique variants - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Sorting coordinates. .tsv ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3014f6ea88a.tsv Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3014f6ea88a.tsv Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014f6ea88a.tsv .tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30132df2303.tsv.gz Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30132df2303.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30132df2303.tsv.gz .tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** save_path suggests .gz output but tabix_index=TRUE Switching output to tabix-indexed format (.bgz). Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa301732d5d89.tsv.bgz Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa301732d5d89.tsv.bgz Converting full summary stats file to tabix format for fast querying... Reading header. Ensuring file is bgzipped. Tabix-indexing file. Reading header. Tabular format detected. Importing tabular bgz file: /tmp/RtmpFPxtDO/fileaa301732d5d89.tsv.bgz .tsv.bgz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3015232ef5d.tsv.bgz Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3015232ef5d.tsv.bgz Converting full summary stats file to tabix format for fast querying... Reading header. Ensuring file is bgzipped. Tabix-indexing file. Reading header. Tabular format detected. Importing tabular bgz file: /tmp/RtmpFPxtDO/fileaa3015232ef5d.tsv.bgz .csv ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa30122bf76ad.csv Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa30122bf76ad.csv Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa30122bf76ad.csv .csv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3017ea24bf.csv.gz Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3017ea24bf.csv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3017ea24bf.csv.gz .vcf ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** save_path suggests VCF output but write_vcf=FALSE. Switching output to tabular format (.tsv.gz). Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3013d91ac28.tsv.gz Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3013d91ac28.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3013d91ac28.tsv.gz .vcf.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** save_path suggests VCF output but write_vcf=FALSE. Switching output to tabular format (.tsv.gz). Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3014ed2c964.tsv.gz Writing in tabular format ==> /tmp/RtmpFPxtDO/fileaa3014ed2c964.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpFPxtDO/fileaa3014ed2c964.tsv.gz .vcf ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3016569efe8.vcf.gz Converting summary statistics to Genomic Ranges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpFPxtDO/fileaa3016569efe8.vcf.gz Reading header. Importing VCF file: /tmp/RtmpFPxtDO/fileaa3016569efe8.vcf.gz Reading VCF file. Standardising column headers. First line of summary statistics file: CHROM POS ID REF ALT QUAL FILTER INFO FORMAT GWAS Removing non-standard columns: QUAL, FILTER, FORMAT Parsing 'GWAS' data column. 1 empty column(s) detected. Formatting INFO column. NOTE: All INFO scores are empty. Replacing all with 1. .vcf ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3017b270199.vcf.gz Converting summary statistics to Genomic Ranges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpFPxtDO/fileaa3017b270199.vcf.gz Compressing with bgzip and indexing with tabix. Reading header. Importing VCF file: /tmp/RtmpFPxtDO/fileaa3017b270199.vcf.bgz Reading VCF file. sumstats_file previously parsed with vcf2df. Standardising column headers. First line of summary statistics file: SNP CHROM BP end width strand paramRangeID REF ALT QUAL FILTER AD_GWAS.1 AD_GWAS.2 DP FT SNP FRQ BETA SE P PARSED Removing non-standard columns: END, WIDTH, STRAND, PARAMRANGEID, QUAL, FILTER, AD_GWAS.1, AD_GWAS.2, DP, FT, PARSED Parsing 'GWAS' data column. 0 empty column(s) detected. .vcf.bgz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deletedupon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpFPxtDO/fileaa3016987ddef.vcf.gz Converting summary statistics to Genomic Ranges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpFPxtDO/fileaa3016987ddef.vcf.gz Compressing with bgzip and indexing with tabix. Reading header. Importing VCF file: /tmp/RtmpFPxtDO/fileaa3016987ddef.vcf.bgz Reading VCF file. sumstats_file previously parsed with vcf2df. Standardising column headers. First line of summary statistics file: SNP CHROM BP end width strand paramRangeID REF ALT QUAL FILTER AD_GWAS.1 AD_GWAS.2 DP FT SNP FRQ BETA SE P PARSED Removing non-standard columns: END, WIDTH, STRAND, PARAMRANGEID, QUAL, FILTER, AD_GWAS.1, AD_GWAS.2, DP, FT, PARSED Parsing 'GWAS' data column. 0 empty column(s) detected. [ FAIL 0 | WARN 5 | SKIP 0 | PASS 122 ] [ FAIL 0 | WARN 5 | SKIP 0 | PASS 122 ] > > proc.time() user system elapsed 570.886 65.223 733.433
MungeSumstats.Rcheck/MungeSumstats-Ex.timings
name | user | system | elapsed | |
download_vcf | 0.001 | 0.000 | 0.001 | |
find_sumstats | 0.001 | 0.000 | 0.001 | |
format_sumstats | 32.878 | 3.708 | 36.658 | |
get_genome_builds | 59.326 | 5.522 | 64.882 | |
import_sumstats | 0.001 | 0.000 | 0.001 | |
index_tabular | 0.017 | 0.012 | 0.030 | |
load_snp_loc_data | 0 | 0 | 0 | |
read_sumstats | 0.002 | 0.000 | 0.003 | |
write_sumstats | 0.003 | 0.000 | 0.004 | |