| Back to Build/check report for BioC 3.20 experimental data |
|
This page was generated on 2025-01-23 15:42 -0500 (Thu, 23 Jan 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4746 |
| 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 | ||||
| Package 379/431 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | ||||||||
| spatialLIBD 1.18.0 (landing page) Leonardo Collado-Torres
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK |  | |||||||
|
To the developers/maintainers of the spatialLIBD package: - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: spatialLIBD |
| Version: 1.18.0 |
| Command: /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:spatialLIBD.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings spatialLIBD_1.18.0.tar.gz |
| StartedAt: 2025-01-23 12:39:10 -0500 (Thu, 23 Jan 2025) |
| EndedAt: 2025-01-23 12:57:00 -0500 (Thu, 23 Jan 2025) |
| EllapsedTime: 1070.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: spatialLIBD.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:spatialLIBD.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings spatialLIBD_1.18.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.20-data-experiment/meat/spatialLIBD.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 LTS
* using session charset: UTF-8
* checking for file ‘spatialLIBD/DESCRIPTION’ ... OK
* this is package ‘spatialLIBD’ version ‘1.18.0’
* 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 ‘spatialLIBD’ 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 code 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 loading without being on the library search path ... 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 LazyData ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
vis_gene 24.631 2.773 27.875
add_images 19.151 2.257 24.022
vis_clus 18.532 2.587 21.579
img_update_all 18.806 1.829 20.664
vis_grid_gene 15.746 2.585 18.691
vis_grid_clus 15.276 2.603 18.335
add_qc_metrics 14.981 2.642 17.795
cluster_import 15.404 2.114 18.809
add_key 15.336 2.112 17.844
cluster_export 15.130 2.133 17.652
geom_spatial 14.502 2.584 17.670
img_edit 14.310 2.076 16.839
frame_limits 14.076 2.003 16.516
vis_clus_p 14.474 1.528 16.358
vis_gene_p 14.434 1.557 17.439
sce_to_spe 14.390 1.453 16.875
img_update 13.970 1.821 16.176
check_spe 13.762 1.720 15.844
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘testthat.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: OK
spatialLIBD.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD INSTALL spatialLIBD ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.20-bioc/R/site-library’ * installing *source* package ‘spatialLIBD’ ... ** using staged installation ** R ** data *** moving datasets to lazyload DB ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices *** copying figures ** 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 (spatialLIBD)
spatialLIBD.Rcheck/tests/testthat.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
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(spatialLIBD)
Loading required package: SpatialExperiment
Loading required package: SingleCellExperiment
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats
Attaching package: 'MatrixGenerics'
The following objects are masked from 'package:matrixStats':
colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
colWeightedMeans, colWeightedMedians, colWeightedSds,
colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
rowWeightedSds, rowWeightedVars
Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
pmin.int, rank, rbind, rownames, sapply, saveRDS, setdiff, table,
tapply, union, unique, unsplit, which.max, which.min
Loading required package: S4Vectors
Attaching package: 'S4Vectors'
The following object is masked from 'package:utils':
findMatches
The following objects are masked from 'package:base':
I, expand.grid, unname
Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Biobase
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: 'Biobase'
The following object is masked from 'package:MatrixGenerics':
rowMedians
The following objects are masked from 'package:matrixStats':
anyMissing, rowMedians
>
> test_check("spatialLIBD")
rgstr_> ## Ensure reproducibility of example data
rgstr_> set.seed(20220907)
rgstr_> ## Generate example data
rgstr_> sce <- scuttle::mockSCE()
rgstr_> ## Add some sample IDs
rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
rgstr_> ## Add a sample-level covariate: age
rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
rgstr_> names(ages) <- LETTERS[1:5]
rgstr_> sce$age <- ages[sce$sample_id]
rgstr_> ## Add gene-level information
rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
rgstr_> ## Pseudo-bulk
rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
rgstr_> colData(sce_pseudo)
DataFrame with 20 rows and 8 columns
Mutation_Status Cell_Cycle Treatment sample_id age
<character> <character> <character> <character> <numeric>
A_G0 NA G0 NA A 19.1872
B_G0 NA G0 NA B 25.3496
C_G0 NA G0 NA C 24.1802
D_G0 NA G0 NA D 15.5211
E_G0 NA G0 NA E 20.9701
... ... ... ... ... ...
A_S NA S NA A 19.1872
B_S NA S NA B 25.3496
C_S NA S NA C 24.1802
D_S NA S NA D 15.5211
E_S NA S NA E 20.9701
registration_variable registration_sample_id ncells
<character> <character> <integer>
A_G0 G0 A 8
B_G0 G0 B 13
C_G0 G0 C 9
D_G0 G0 D 7
E_G0 G0 E 10
... ... ... ...
A_S S A 12
B_S S B 8
C_S S C 7
D_S S D 14
E_S S E 11
rgstr_> ## Ensure reproducibility of example data
rgstr_> set.seed(20220907)
rgstr_> ## Generate example data
rgstr_> sce <- scuttle::mockSCE()
rgstr_> ## Add some sample IDs
rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
rgstr_> ## Add a sample-level covariate: age
rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
rgstr_> names(ages) <- LETTERS[1:5]
rgstr_> sce$age <- ages[sce$sample_id]
rgstr_> ## Add gene-level information
rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
rgstr_> ## Pseudo-bulk
rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
rgstr_> colData(sce_pseudo)
DataFrame with 20 rows and 8 columns
Mutation_Status Cell_Cycle Treatment sample_id age
<character> <character> <character> <character> <numeric>
A_G0 NA G0 NA A 19.1872
B_G0 NA G0 NA B 25.3496
C_G0 NA G0 NA C 24.1802
D_G0 NA G0 NA D 15.5211
E_G0 NA G0 NA E 20.9701
... ... ... ... ... ...
A_S NA S NA A 19.1872
B_S NA S NA B 25.3496
C_S NA S NA C 24.1802
D_S NA S NA D 15.5211
E_S NA S NA E 20.9701
registration_variable registration_sample_id ncells
<character> <character> <integer>
A_G0 G0 A 8
B_G0 G0 B 13
C_G0 G0 C 9
D_G0 G0 D 7
E_G0 G0 E 10
... ... ... ...
A_S S A 12
B_S S B 8
C_S S C 7
D_S S D 14
E_S S E 11
rgst__> example("registration_model", package = "spatialLIBD")
rgstr_> example("registration_pseudobulk", package = "spatialLIBD")
rgstr_> ## Ensure reproducibility of example data
rgstr_> set.seed(20220907)
rgstr_> ## Generate example data
rgstr_> sce <- scuttle::mockSCE()
rgstr_> ## Add some sample IDs
rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE)
rgstr_> ## Add a sample-level covariate: age
rgstr_> ages <- rnorm(5, mean = 20, sd = 4)
rgstr_> names(ages) <- LETTERS[1:5]
rgstr_> sce$age <- ages[sce$sample_id]
rgstr_> ## Add gene-level information
rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce)))
rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce)))
rgstr_> ## Pseudo-bulk
rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL)
rgstr_> colData(sce_pseudo)
DataFrame with 20 rows and 8 columns
Mutation_Status Cell_Cycle Treatment sample_id age
<character> <character> <character> <character> <numeric>
A_G0 NA G0 NA A 19.1872
B_G0 NA G0 NA B 25.3496
C_G0 NA G0 NA C 24.1802
D_G0 NA G0 NA D 15.5211
E_G0 NA G0 NA E 20.9701
... ... ... ... ... ...
A_S NA S NA A 19.1872
B_S NA S NA B 25.3496
C_S NA S NA C 24.1802
D_S NA S NA D 15.5211
E_S NA S NA E 20.9701
registration_variable registration_sample_id ncells
<character> <character> <integer>
A_G0 G0 A 8
B_G0 G0 B 13
C_G0 G0 C 9
D_G0 G0 D 7
E_G0 G0 E 10
... ... ... ...
A_S S A 12
B_S S B 8
C_S S C 7
D_S S D 14
E_S S E 11
rgstr_> registration_mod <- registration_model(sce_pseudo, "age")
rgstr_> head(registration_mod)
registration_variableG0 registration_variableG1 registration_variableG2M
A_G0 1 0 0
B_G0 1 0 0
C_G0 1 0 0
D_G0 1 0 0
E_G0 1 0 0
A_G1 0 1 0
registration_variableS age
A_G0 0 19.18719
B_G0 0 25.34965
C_G0 0 24.18019
D_G0 0 15.52107
E_G0 0 20.97006
A_G1 0 19.18719
rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod)
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 33 ]
>
> proc.time()
user system elapsed
87.886 8.241 97.904
spatialLIBD.Rcheck/spatialLIBD-Ex.timings
| name | user | system | elapsed | |
| add10xVisiumAnalysis | 0.000 | 0.000 | 0.001 | |
| add_images | 19.151 | 2.257 | 24.022 | |
| add_key | 15.336 | 2.112 | 17.844 | |
| add_qc_metrics | 14.981 | 2.642 | 17.795 | |
| annotate_registered_clusters | 1.121 | 0.069 | 1.355 | |
| check_modeling_results | 1.096 | 0.079 | 1.335 | |
| check_sce | 3.292 | 0.153 | 3.607 | |
| check_sce_layer | 1.186 | 0.095 | 1.444 | |
| check_spe | 13.762 | 1.720 | 15.844 | |
| cluster_export | 15.130 | 2.133 | 17.652 | |
| cluster_import | 15.404 | 2.114 | 18.809 | |
| enough_ram | 0.005 | 0.004 | 0.008 | |
| fetch_data | 1.197 | 0.127 | 1.508 | |
| frame_limits | 14.076 | 2.003 | 16.516 | |
| gene_set_enrichment | 1.386 | 0.437 | 1.988 | |
| gene_set_enrichment_plot | 1.474 | 0.250 | 1.882 | |
| geom_spatial | 14.502 | 2.584 | 17.670 | |
| get_colors | 1.270 | 0.199 | 1.559 | |
| img_edit | 14.310 | 2.076 | 16.839 | |
| img_update | 13.970 | 1.821 | 16.176 | |
| img_update_all | 18.806 | 1.829 | 20.664 | |
| layer_boxplot | 3.242 | 0.301 | 3.862 | |
| layer_matrix_plot | 0.009 | 0.001 | 0.010 | |
| layer_stat_cor | 1.102 | 0.041 | 1.311 | |
| layer_stat_cor_plot | 1.228 | 0.057 | 1.450 | |
| locate_images | 0 | 0 | 0 | |
| read10xVisiumAnalysis | 0 | 0 | 0 | |
| read10xVisiumWrapper | 0 | 0 | 0 | |
| registration_block_cor | 3.805 | 0.313 | 4.118 | |
| registration_model | 0.625 | 0.012 | 0.638 | |
| registration_pseudobulk | 0.597 | 0.030 | 0.627 | |
| registration_stats_anova | 2.756 | 0.063 | 2.820 | |
| registration_stats_enrichment | 2.966 | 0.120 | 3.084 | |
| registration_stats_pairwise | 2.764 | 0.024 | 2.788 | |
| registration_wrapper | 4.122 | 0.066 | 4.188 | |
| run_app | 0.000 | 0.000 | 0.001 | |
| sce_to_spe | 14.390 | 1.453 | 16.875 | |
| sig_genes_extract | 2.573 | 0.233 | 3.127 | |
| sig_genes_extract_all | 3.419 | 0.285 | 4.047 | |
| sort_clusters | 0.009 | 0.001 | 0.009 | |
| vis_clus | 18.532 | 2.587 | 21.579 | |
| vis_clus_p | 14.474 | 1.528 | 16.358 | |
| vis_gene | 24.631 | 2.773 | 27.875 | |
| vis_gene_p | 14.434 | 1.557 | 17.439 | |
| vis_grid_clus | 15.276 | 2.603 | 18.335 | |
| vis_grid_gene | 15.746 | 2.585 | 18.691 | |