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CHECK report for MultiAssayExperiment on malbec1

This page was generated on 2019-04-16 11:51:59 -0400 (Tue, 16 Apr 2019).

Package 1019/1649HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
MultiAssayExperiment 1.8.3
Marcel Ramos
Snapshot Date: 2019-04-15 17:01:12 -0400 (Mon, 15 Apr 2019)
URL: https://git.bioconductor.org/packages/MultiAssayExperiment
Branch: RELEASE_3_8
Last Commit: 390538d
Last Changed Date: 2019-02-14 12:37:06 -0400 (Thu, 14 Feb 2019)
malbec1 Linux (Ubuntu 16.04.6 LTS) / x86_64  OK  OK [ OK ]UNNEEDED, same version exists in internal repository
merida1 OS X 10.11.6 El Capitan / x86_64  OK  OK  OK  OK UNNEEDED, same version exists in internal repository

Summary

Package: MultiAssayExperiment
Version: 1.8.3
Command: /home/biocbuild/bbs-3.8-bioc/R/bin/R CMD check --install=check:MultiAssayExperiment.install-out.txt --library=/home/biocbuild/bbs-3.8-bioc/R/library --no-vignettes --timings MultiAssayExperiment_1.8.3.tar.gz
StartedAt: 2019-04-16 01:38:50 -0400 (Tue, 16 Apr 2019)
EndedAt: 2019-04-16 01:41:54 -0400 (Tue, 16 Apr 2019)
EllapsedTime: 184.0 seconds
RetCode: 0
Status:  OK 
CheckDir: MultiAssayExperiment.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.8-bioc/R/bin/R CMD check --install=check:MultiAssayExperiment.install-out.txt --library=/home/biocbuild/bbs-3.8-bioc/R/library --no-vignettes --timings MultiAssayExperiment_1.8.3.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.8-bioc/meat/MultiAssayExperiment.Rcheck’
* using R version 3.5.3 (2019-03-11)
* using platform: x86_64-pc-linux-gnu (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘MultiAssayExperiment/DESCRIPTION’ ... OK
* this is package ‘MultiAssayExperiment’ version ‘1.8.3’
* 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 ‘MultiAssayExperiment’ 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 ... NOTE
Unexported objects imported by ':::' calls:
  ‘BiocGenerics:::replaceSlots’ ‘S4Vectors:::selectSome’
  See the note in ?`:::` about the use of this operator.
* 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 files in ‘vignettes’ ... OK
* checking examples ... OK
* 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: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.8-bioc/meat/MultiAssayExperiment.Rcheck/00check.log’
for details.

Installation output

MultiAssayExperiment.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.8-bioc/R/bin/R CMD INSTALL MultiAssayExperiment
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.8-bioc/R/library’
* installing *source* package ‘MultiAssayExperiment’ ...
** R
** data
*** moving datasets to lazyload DB
** 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
* DONE (MultiAssayExperiment)

Tests output

MultiAssayExperiment.Rcheck/tests/testthat.Rout


R version 3.5.3 (2019-03-11) -- "Great Truth"
Copyright (C) 2019 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(MultiAssayExperiment)
Loading required package: SummarizedExperiment
Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

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, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:base':

    expand.grid

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")'.

Loading required package: DelayedArray
Loading required package: matrixStats

Attaching package: 'matrixStats'

The following objects are masked from 'package:Biobase':

    anyMissing, rowMedians

Loading required package: BiocParallel

Attaching package: 'DelayedArray'

The following objects are masked from 'package:matrixStats':

    colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges

The following objects are masked from 'package:base':

    aperm, apply

> 
> test_check("MultiAssayExperiment")

MltAsE> ## Run the example ExperimentList
MltAsE> example("ExperimentList")

ExprmL> ## Create an empty ExperimentList instance
ExprmL> ExperimentList()
ExperimentList class object of length 0:  

ExprmL> ## Create array matrix and AnnotatedDataFrame to create an ExpressionSet class
ExprmL> arraydat <- matrix(data = seq(101, length.out = 20), ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000294241", "ENST00000355076",
ExprmL+         "ENST00000383706","ENST00000234812", "ENST00000383323"),
ExprmL+         c("array1", "array2", "array3", "array4")
ExprmL+     ))

ExprmL> colDat <- data.frame(slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4"))

ExprmL> ## SummarizedExperiment constructor
ExprmL> exprdat <- SummarizedExperiment::SummarizedExperiment(arraydat,
ExprmL+     colData = colDat)

ExprmL> ## Create a sample methylation dataset
ExprmL> methyldat <- matrix(data = seq(1, length.out = 25), ncol = 5,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000355076", "ENST00000383706",
ExprmL+           "ENST00000383323", "ENST00000234812", "ENST00000294241"),
ExprmL+         c("methyl1", "methyl2", "methyl3",
ExprmL+           "methyl4", "methyl5")
ExprmL+     ))

ExprmL> ## Create a sample RNASeqGene dataset
ExprmL> rnadat <- matrix(
ExprmL+     data = sample(c(46851, 5, 19, 13, 2197, 507,
ExprmL+         84318, 126, 17, 21, 23979, 614), size = 20, replace = TRUE),
ExprmL+     ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("XIST", "RPS4Y1", "KDM5D", "ENST00000383323", "ENST00000234812"),
ExprmL+         c("samparray1", "samparray2", "samparray3", "samparray4")
ExprmL+     ))

ExprmL> ## Create a mock RangedSummarizedExperiment from a data.frame
ExprmL> rangedat <- data.frame(chr="chr2", start = 11:15, end = 12:16,
ExprmL+     strand = c("+", "-", "+", "*", "."),
ExprmL+     samp0 = c(0,0,1,1,1), samp1 = c(1,0,1,0,1), samp2 = c(0,1,0,1,0),
ExprmL+     row.names = paste0("GENE", letters[5:1]))

ExprmL> rangeSE <- SummarizedExperiment::makeSummarizedExperimentFromDataFrame(rangedat)

ExprmL> ## Combine to a named list and call the ExperimentList constructor function
ExprmL> assayList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

ExprmL> ## Use the ExperimentList constructor
ExprmL> ExpList <- ExperimentList(assayList)

MltAsE> ## Create sample maps for each experiment
MltAsE> exprmap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("array1", "array2", "array3", "array4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> methylmap <- data.frame(
MltAsE+     primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> rnamap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Bob", "Barbara"),
MltAsE+     colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> gistmap <- data.frame(
MltAsE+     primary = c("Jack", "Bob", "Jill"),
MltAsE+     colname = c("samp0", "samp1", "samp2"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> ## Combine as a named list and convert to a DataFrame
MltAsE> maplist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> sampMap <- listToMap(maplist)

MltAsE> ## Create an example phenotype data
MltAsE> colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
MltAsE+     row.names = c("Jack", "Jill", "Bob", "Barbara"))

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
MltAsE+     sampleMap = sampMap)

MltAsE> ## Run the example ExperimentList
MltAsE> example("ExperimentList")

ExprmL> ## Create an empty ExperimentList instance
ExprmL> ExperimentList()
ExperimentList class object of length 0:  

ExprmL> ## Create array matrix and AnnotatedDataFrame to create an ExpressionSet class
ExprmL> arraydat <- matrix(data = seq(101, length.out = 20), ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000294241", "ENST00000355076",
ExprmL+         "ENST00000383706","ENST00000234812", "ENST00000383323"),
ExprmL+         c("array1", "array2", "array3", "array4")
ExprmL+     ))

ExprmL> colDat <- data.frame(slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4"))

ExprmL> ## SummarizedExperiment constructor
ExprmL> exprdat <- SummarizedExperiment::SummarizedExperiment(arraydat,
ExprmL+     colData = colDat)

ExprmL> ## Create a sample methylation dataset
ExprmL> methyldat <- matrix(data = seq(1, length.out = 25), ncol = 5,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000355076", "ENST00000383706",
ExprmL+           "ENST00000383323", "ENST00000234812", "ENST00000294241"),
ExprmL+         c("methyl1", "methyl2", "methyl3",
ExprmL+           "methyl4", "methyl5")
ExprmL+     ))

ExprmL> ## Create a sample RNASeqGene dataset
ExprmL> rnadat <- matrix(
ExprmL+     data = sample(c(46851, 5, 19, 13, 2197, 507,
ExprmL+         84318, 126, 17, 21, 23979, 614), size = 20, replace = TRUE),
ExprmL+     ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("XIST", "RPS4Y1", "KDM5D", "ENST00000383323", "ENST00000234812"),
ExprmL+         c("samparray1", "samparray2", "samparray3", "samparray4")
ExprmL+     ))

ExprmL> ## Create a mock RangedSummarizedExperiment from a data.frame
ExprmL> rangedat <- data.frame(chr="chr2", start = 11:15, end = 12:16,
ExprmL+     strand = c("+", "-", "+", "*", "."),
ExprmL+     samp0 = c(0,0,1,1,1), samp1 = c(1,0,1,0,1), samp2 = c(0,1,0,1,0),
ExprmL+     row.names = paste0("GENE", letters[5:1]))

ExprmL> rangeSE <- SummarizedExperiment::makeSummarizedExperimentFromDataFrame(rangedat)

ExprmL> ## Combine to a named list and call the ExperimentList constructor function
ExprmL> assayList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

ExprmL> ## Use the ExperimentList constructor
ExprmL> ExpList <- ExperimentList(assayList)

MltAsE> ## Create sample maps for each experiment
MltAsE> exprmap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("array1", "array2", "array3", "array4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> methylmap <- data.frame(
MltAsE+     primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> rnamap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Bob", "Barbara"),
MltAsE+     colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> gistmap <- data.frame(
MltAsE+     primary = c("Jack", "Bob", "Jill"),
MltAsE+     colname = c("samp0", "samp1", "samp2"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> ## Combine as a named list and convert to a DataFrame
MltAsE> maplist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> sampMap <- listToMap(maplist)

MltAsE> ## Create an example phenotype data
MltAsE> colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
MltAsE+     row.names = c("Jack", "Jill", "Bob", "Barbara"))

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
MltAsE+     sampleMap = sampMap)

MltAsE> ## Run the example ExperimentList
MltAsE> example("ExperimentList")

ExprmL> ## Create an empty ExperimentList instance
ExprmL> ExperimentList()
ExperimentList class object of length 0:  

ExprmL> ## Create array matrix and AnnotatedDataFrame to create an ExpressionSet class
ExprmL> arraydat <- matrix(data = seq(101, length.out = 20), ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000294241", "ENST00000355076",
ExprmL+         "ENST00000383706","ENST00000234812", "ENST00000383323"),
ExprmL+         c("array1", "array2", "array3", "array4")
ExprmL+     ))

ExprmL> colDat <- data.frame(slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4"))

ExprmL> ## SummarizedExperiment constructor
ExprmL> exprdat <- SummarizedExperiment::SummarizedExperiment(arraydat,
ExprmL+     colData = colDat)

ExprmL> ## Create a sample methylation dataset
ExprmL> methyldat <- matrix(data = seq(1, length.out = 25), ncol = 5,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000355076", "ENST00000383706",
ExprmL+           "ENST00000383323", "ENST00000234812", "ENST00000294241"),
ExprmL+         c("methyl1", "methyl2", "methyl3",
ExprmL+           "methyl4", "methyl5")
ExprmL+     ))

ExprmL> ## Create a sample RNASeqGene dataset
ExprmL> rnadat <- matrix(
ExprmL+     data = sample(c(46851, 5, 19, 13, 2197, 507,
ExprmL+         84318, 126, 17, 21, 23979, 614), size = 20, replace = TRUE),
ExprmL+     ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("XIST", "RPS4Y1", "KDM5D", "ENST00000383323", "ENST00000234812"),
ExprmL+         c("samparray1", "samparray2", "samparray3", "samparray4")
ExprmL+     ))

ExprmL> ## Create a mock RangedSummarizedExperiment from a data.frame
ExprmL> rangedat <- data.frame(chr="chr2", start = 11:15, end = 12:16,
ExprmL+     strand = c("+", "-", "+", "*", "."),
ExprmL+     samp0 = c(0,0,1,1,1), samp1 = c(1,0,1,0,1), samp2 = c(0,1,0,1,0),
ExprmL+     row.names = paste0("GENE", letters[5:1]))

ExprmL> rangeSE <- SummarizedExperiment::makeSummarizedExperimentFromDataFrame(rangedat)

ExprmL> ## Combine to a named list and call the ExperimentList constructor function
ExprmL> assayList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

ExprmL> ## Use the ExperimentList constructor
ExprmL> ExpList <- ExperimentList(assayList)

MltAsE> ## Create sample maps for each experiment
MltAsE> exprmap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("array1", "array2", "array3", "array4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> methylmap <- data.frame(
MltAsE+     primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> rnamap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Bob", "Barbara"),
MltAsE+     colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> gistmap <- data.frame(
MltAsE+     primary = c("Jack", "Bob", "Jill"),
MltAsE+     colname = c("samp0", "samp1", "samp2"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> ## Combine as a named list and convert to a DataFrame
MltAsE> maplist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> sampMap <- listToMap(maplist)

MltAsE> ## Create an example phenotype data
MltAsE> colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
MltAsE+     row.names = c("Jack", "Jill", "Bob", "Barbara"))

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
MltAsE+     sampleMap = sampMap)

MltAsE> ## Run the example ExperimentList
MltAsE> example("ExperimentList")

ExprmL> ## Create an empty ExperimentList instance
ExprmL> ExperimentList()
ExperimentList class object of length 0:  

ExprmL> ## Create array matrix and AnnotatedDataFrame to create an ExpressionSet class
ExprmL> arraydat <- matrix(data = seq(101, length.out = 20), ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000294241", "ENST00000355076",
ExprmL+         "ENST00000383706","ENST00000234812", "ENST00000383323"),
ExprmL+         c("array1", "array2", "array3", "array4")
ExprmL+     ))

ExprmL> colDat <- data.frame(slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4"))

ExprmL> ## SummarizedExperiment constructor
ExprmL> exprdat <- SummarizedExperiment::SummarizedExperiment(arraydat,
ExprmL+     colData = colDat)

ExprmL> ## Create a sample methylation dataset
ExprmL> methyldat <- matrix(data = seq(1, length.out = 25), ncol = 5,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000355076", "ENST00000383706",
ExprmL+           "ENST00000383323", "ENST00000234812", "ENST00000294241"),
ExprmL+         c("methyl1", "methyl2", "methyl3",
ExprmL+           "methyl4", "methyl5")
ExprmL+     ))

ExprmL> ## Create a sample RNASeqGene dataset
ExprmL> rnadat <- matrix(
ExprmL+     data = sample(c(46851, 5, 19, 13, 2197, 507,
ExprmL+         84318, 126, 17, 21, 23979, 614), size = 20, replace = TRUE),
ExprmL+     ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("XIST", "RPS4Y1", "KDM5D", "ENST00000383323", "ENST00000234812"),
ExprmL+         c("samparray1", "samparray2", "samparray3", "samparray4")
ExprmL+     ))

ExprmL> ## Create a mock RangedSummarizedExperiment from a data.frame
ExprmL> rangedat <- data.frame(chr="chr2", start = 11:15, end = 12:16,
ExprmL+     strand = c("+", "-", "+", "*", "."),
ExprmL+     samp0 = c(0,0,1,1,1), samp1 = c(1,0,1,0,1), samp2 = c(0,1,0,1,0),
ExprmL+     row.names = paste0("GENE", letters[5:1]))

ExprmL> rangeSE <- SummarizedExperiment::makeSummarizedExperimentFromDataFrame(rangedat)

ExprmL> ## Combine to a named list and call the ExperimentList constructor function
ExprmL> assayList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

ExprmL> ## Use the ExperimentList constructor
ExprmL> ExpList <- ExperimentList(assayList)

MltAsE> ## Create sample maps for each experiment
MltAsE> exprmap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("array1", "array2", "array3", "array4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> methylmap <- data.frame(
MltAsE+     primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> rnamap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Bob", "Barbara"),
MltAsE+     colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> gistmap <- data.frame(
MltAsE+     primary = c("Jack", "Bob", "Jill"),
MltAsE+     colname = c("samp0", "samp1", "samp2"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> ## Combine as a named list and convert to a DataFrame
MltAsE> maplist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> sampMap <- listToMap(maplist)

MltAsE> ## Create an example phenotype data
MltAsE> colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
MltAsE+     row.names = c("Jack", "Jill", "Bob", "Barbara"))

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
MltAsE+     sampleMap = sampMap)

MltAsE> ## Run the example ExperimentList
MltAsE> example("ExperimentList")

ExprmL> ## Create an empty ExperimentList instance
ExprmL> ExperimentList()
ExperimentList class object of length 0:  

ExprmL> ## Create array matrix and AnnotatedDataFrame to create an ExpressionSet class
ExprmL> arraydat <- matrix(data = seq(101, length.out = 20), ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000294241", "ENST00000355076",
ExprmL+         "ENST00000383706","ENST00000234812", "ENST00000383323"),
ExprmL+         c("array1", "array2", "array3", "array4")
ExprmL+     ))

ExprmL> colDat <- data.frame(slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4"))

ExprmL> ## SummarizedExperiment constructor
ExprmL> exprdat <- SummarizedExperiment::SummarizedExperiment(arraydat,
ExprmL+     colData = colDat)

ExprmL> ## Create a sample methylation dataset
ExprmL> methyldat <- matrix(data = seq(1, length.out = 25), ncol = 5,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000355076", "ENST00000383706",
ExprmL+           "ENST00000383323", "ENST00000234812", "ENST00000294241"),
ExprmL+         c("methyl1", "methyl2", "methyl3",
ExprmL+           "methyl4", "methyl5")
ExprmL+     ))

ExprmL> ## Create a sample RNASeqGene dataset
ExprmL> rnadat <- matrix(
ExprmL+     data = sample(c(46851, 5, 19, 13, 2197, 507,
ExprmL+         84318, 126, 17, 21, 23979, 614), size = 20, replace = TRUE),
ExprmL+     ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("XIST", "RPS4Y1", "KDM5D", "ENST00000383323", "ENST00000234812"),
ExprmL+         c("samparray1", "samparray2", "samparray3", "samparray4")
ExprmL+     ))

ExprmL> ## Create a mock RangedSummarizedExperiment from a data.frame
ExprmL> rangedat <- data.frame(chr="chr2", start = 11:15, end = 12:16,
ExprmL+     strand = c("+", "-", "+", "*", "."),
ExprmL+     samp0 = c(0,0,1,1,1), samp1 = c(1,0,1,0,1), samp2 = c(0,1,0,1,0),
ExprmL+     row.names = paste0("GENE", letters[5:1]))

ExprmL> rangeSE <- SummarizedExperiment::makeSummarizedExperimentFromDataFrame(rangedat)

ExprmL> ## Combine to a named list and call the ExperimentList constructor function
ExprmL> assayList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

ExprmL> ## Use the ExperimentList constructor
ExprmL> ExpList <- ExperimentList(assayList)

MltAsE> ## Create sample maps for each experiment
MltAsE> exprmap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("array1", "array2", "array3", "array4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> methylmap <- data.frame(
MltAsE+     primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> rnamap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Bob", "Barbara"),
MltAsE+     colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> gistmap <- data.frame(
MltAsE+     primary = c("Jack", "Bob", "Jill"),
MltAsE+     colname = c("samp0", "samp1", "samp2"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> ## Combine as a named list and convert to a DataFrame
MltAsE> maplist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> sampMap <- listToMap(maplist)

MltAsE> ## Create an example phenotype data
MltAsE> colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
MltAsE+     row.names = c("Jack", "Jill", "Bob", "Barbara"))

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
MltAsE+     sampleMap = sampMap)

MltAsE> ## Run the example ExperimentList
MltAsE> example("ExperimentList")

ExprmL> ## Create an empty ExperimentList instance
ExprmL> ExperimentList()
ExperimentList class object of length 0:  

ExprmL> ## Create array matrix and AnnotatedDataFrame to create an ExpressionSet class
ExprmL> arraydat <- matrix(data = seq(101, length.out = 20), ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000294241", "ENST00000355076",
ExprmL+         "ENST00000383706","ENST00000234812", "ENST00000383323"),
ExprmL+         c("array1", "array2", "array3", "array4")
ExprmL+     ))

ExprmL> colDat <- data.frame(slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4"))

ExprmL> ## SummarizedExperiment constructor
ExprmL> exprdat <- SummarizedExperiment::SummarizedExperiment(arraydat,
ExprmL+     colData = colDat)

ExprmL> ## Create a sample methylation dataset
ExprmL> methyldat <- matrix(data = seq(1, length.out = 25), ncol = 5,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000355076", "ENST00000383706",
ExprmL+           "ENST00000383323", "ENST00000234812", "ENST00000294241"),
ExprmL+         c("methyl1", "methyl2", "methyl3",
ExprmL+           "methyl4", "methyl5")
ExprmL+     ))

ExprmL> ## Create a sample RNASeqGene dataset
ExprmL> rnadat <- matrix(
ExprmL+     data = sample(c(46851, 5, 19, 13, 2197, 507,
ExprmL+         84318, 126, 17, 21, 23979, 614), size = 20, replace = TRUE),
ExprmL+     ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("XIST", "RPS4Y1", "KDM5D", "ENST00000383323", "ENST00000234812"),
ExprmL+         c("samparray1", "samparray2", "samparray3", "samparray4")
ExprmL+     ))

ExprmL> ## Create a mock RangedSummarizedExperiment from a data.frame
ExprmL> rangedat <- data.frame(chr="chr2", start = 11:15, end = 12:16,
ExprmL+     strand = c("+", "-", "+", "*", "."),
ExprmL+     samp0 = c(0,0,1,1,1), samp1 = c(1,0,1,0,1), samp2 = c(0,1,0,1,0),
ExprmL+     row.names = paste0("GENE", letters[5:1]))

ExprmL> rangeSE <- SummarizedExperiment::makeSummarizedExperimentFromDataFrame(rangedat)

ExprmL> ## Combine to a named list and call the ExperimentList constructor function
ExprmL> assayList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

ExprmL> ## Use the ExperimentList constructor
ExprmL> ExpList <- ExperimentList(assayList)

MltAsE> ## Create sample maps for each experiment
MltAsE> exprmap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("array1", "array2", "array3", "array4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> methylmap <- data.frame(
MltAsE+     primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> rnamap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Bob", "Barbara"),
MltAsE+     colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> gistmap <- data.frame(
MltAsE+     primary = c("Jack", "Bob", "Jill"),
MltAsE+     colname = c("samp0", "samp1", "samp2"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> ## Combine as a named list and convert to a DataFrame
MltAsE> maplist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> sampMap <- listToMap(maplist)

MltAsE> ## Create an example phenotype data
MltAsE> colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
MltAsE+     row.names = c("Jack", "Jill", "Bob", "Barbara"))

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
MltAsE+     sampleMap = sampMap)

MltAsE> ## Run the example ExperimentList
MltAsE> example("ExperimentList")

ExprmL> ## Create an empty ExperimentList instance
ExprmL> ExperimentList()
ExperimentList class object of length 0:  

ExprmL> ## Create array matrix and AnnotatedDataFrame to create an ExpressionSet class
ExprmL> arraydat <- matrix(data = seq(101, length.out = 20), ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000294241", "ENST00000355076",
ExprmL+         "ENST00000383706","ENST00000234812", "ENST00000383323"),
ExprmL+         c("array1", "array2", "array3", "array4")
ExprmL+     ))

ExprmL> colDat <- data.frame(slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4"))

ExprmL> ## SummarizedExperiment constructor
ExprmL> exprdat <- SummarizedExperiment::SummarizedExperiment(arraydat,
ExprmL+     colData = colDat)

ExprmL> ## Create a sample methylation dataset
ExprmL> methyldat <- matrix(data = seq(1, length.out = 25), ncol = 5,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000355076", "ENST00000383706",
ExprmL+           "ENST00000383323", "ENST00000234812", "ENST00000294241"),
ExprmL+         c("methyl1", "methyl2", "methyl3",
ExprmL+           "methyl4", "methyl5")
ExprmL+     ))

ExprmL> ## Create a sample RNASeqGene dataset
ExprmL> rnadat <- matrix(
ExprmL+     data = sample(c(46851, 5, 19, 13, 2197, 507,
ExprmL+         84318, 126, 17, 21, 23979, 614), size = 20, replace = TRUE),
ExprmL+     ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("XIST", "RPS4Y1", "KDM5D", "ENST00000383323", "ENST00000234812"),
ExprmL+         c("samparray1", "samparray2", "samparray3", "samparray4")
ExprmL+     ))

ExprmL> ## Create a mock RangedSummarizedExperiment from a data.frame
ExprmL> rangedat <- data.frame(chr="chr2", start = 11:15, end = 12:16,
ExprmL+     strand = c("+", "-", "+", "*", "."),
ExprmL+     samp0 = c(0,0,1,1,1), samp1 = c(1,0,1,0,1), samp2 = c(0,1,0,1,0),
ExprmL+     row.names = paste0("GENE", letters[5:1]))

ExprmL> rangeSE <- SummarizedExperiment::makeSummarizedExperimentFromDataFrame(rangedat)

ExprmL> ## Combine to a named list and call the ExperimentList constructor function
ExprmL> assayList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

ExprmL> ## Use the ExperimentList constructor
ExprmL> ExpList <- ExperimentList(assayList)

MltAsE> ## Create sample maps for each experiment
MltAsE> exprmap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("array1", "array2", "array3", "array4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> methylmap <- data.frame(
MltAsE+     primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> rnamap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Bob", "Barbara"),
MltAsE+     colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> gistmap <- data.frame(
MltAsE+     primary = c("Jack", "Bob", "Jill"),
MltAsE+     colname = c("samp0", "samp1", "samp2"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> ## Combine as a named list and convert to a DataFrame
MltAsE> maplist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> sampMap <- listToMap(maplist)

MltAsE> ## Create an example phenotype data
MltAsE> colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
MltAsE+     row.names = c("Jack", "Jill", "Bob", "Barbara"))

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
MltAsE+     sampleMap = sampMap)

MltAsE> ## Run the example ExperimentList
MltAsE> example("ExperimentList")

ExprmL> ## Create an empty ExperimentList instance
ExprmL> ExperimentList()
ExperimentList class object of length 0:  

ExprmL> ## Create array matrix and AnnotatedDataFrame to create an ExpressionSet class
ExprmL> arraydat <- matrix(data = seq(101, length.out = 20), ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000294241", "ENST00000355076",
ExprmL+         "ENST00000383706","ENST00000234812", "ENST00000383323"),
ExprmL+         c("array1", "array2", "array3", "array4")
ExprmL+     ))

ExprmL> colDat <- data.frame(slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4"))

ExprmL> ## SummarizedExperiment constructor
ExprmL> exprdat <- SummarizedExperiment::SummarizedExperiment(arraydat,
ExprmL+     colData = colDat)

ExprmL> ## Create a sample methylation dataset
ExprmL> methyldat <- matrix(data = seq(1, length.out = 25), ncol = 5,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000355076", "ENST00000383706",
ExprmL+           "ENST00000383323", "ENST00000234812", "ENST00000294241"),
ExprmL+         c("methyl1", "methyl2", "methyl3",
ExprmL+           "methyl4", "methyl5")
ExprmL+     ))

ExprmL> ## Create a sample RNASeqGene dataset
ExprmL> rnadat <- matrix(
ExprmL+     data = sample(c(46851, 5, 19, 13, 2197, 507,
ExprmL+         84318, 126, 17, 21, 23979, 614), size = 20, replace = TRUE),
ExprmL+     ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("XIST", "RPS4Y1", "KDM5D", "ENST00000383323", "ENST00000234812"),
ExprmL+         c("samparray1", "samparray2", "samparray3", "samparray4")
ExprmL+     ))

ExprmL> ## Create a mock RangedSummarizedExperiment from a data.frame
ExprmL> rangedat <- data.frame(chr="chr2", start = 11:15, end = 12:16,
ExprmL+     strand = c("+", "-", "+", "*", "."),
ExprmL+     samp0 = c(0,0,1,1,1), samp1 = c(1,0,1,0,1), samp2 = c(0,1,0,1,0),
ExprmL+     row.names = paste0("GENE", letters[5:1]))

ExprmL> rangeSE <- SummarizedExperiment::makeSummarizedExperimentFromDataFrame(rangedat)

ExprmL> ## Combine to a named list and call the ExperimentList constructor function
ExprmL> assayList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

ExprmL> ## Use the ExperimentList constructor
ExprmL> ExpList <- ExperimentList(assayList)

MltAsE> ## Create sample maps for each experiment
MltAsE> exprmap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("array1", "array2", "array3", "array4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> methylmap <- data.frame(
MltAsE+     primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> rnamap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Bob", "Barbara"),
MltAsE+     colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> gistmap <- data.frame(
MltAsE+     primary = c("Jack", "Bob", "Jill"),
MltAsE+     colname = c("samp0", "samp1", "samp2"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> ## Combine as a named list and convert to a DataFrame
MltAsE> maplist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> sampMap <- listToMap(maplist)

MltAsE> ## Create an example phenotype data
MltAsE> colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
MltAsE+     row.names = c("Jack", "Jill", "Bob", "Barbara"))

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
MltAsE+     sampleMap = sampMap)

MltAsE> ## Run the example ExperimentList
MltAsE> example("ExperimentList")

ExprmL> ## Create an empty ExperimentList instance
ExprmL> ExperimentList()
ExperimentList class object of length 0:  

ExprmL> ## Create array matrix and AnnotatedDataFrame to create an ExpressionSet class
ExprmL> arraydat <- matrix(data = seq(101, length.out = 20), ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000294241", "ENST00000355076",
ExprmL+         "ENST00000383706","ENST00000234812", "ENST00000383323"),
ExprmL+         c("array1", "array2", "array3", "array4")
ExprmL+     ))

ExprmL> colDat <- data.frame(slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4"))

ExprmL> ## SummarizedExperiment constructor
ExprmL> exprdat <- SummarizedExperiment::SummarizedExperiment(arraydat,
ExprmL+     colData = colDat)

ExprmL> ## Create a sample methylation dataset
ExprmL> methyldat <- matrix(data = seq(1, length.out = 25), ncol = 5,
ExprmL+     dimnames = list(
ExprmL+         c("ENST00000355076", "ENST00000383706",
ExprmL+           "ENST00000383323", "ENST00000234812", "ENST00000294241"),
ExprmL+         c("methyl1", "methyl2", "methyl3",
ExprmL+           "methyl4", "methyl5")
ExprmL+     ))

ExprmL> ## Create a sample RNASeqGene dataset
ExprmL> rnadat <- matrix(
ExprmL+     data = sample(c(46851, 5, 19, 13, 2197, 507,
ExprmL+         84318, 126, 17, 21, 23979, 614), size = 20, replace = TRUE),
ExprmL+     ncol = 4,
ExprmL+     dimnames = list(
ExprmL+         c("XIST", "RPS4Y1", "KDM5D", "ENST00000383323", "ENST00000234812"),
ExprmL+         c("samparray1", "samparray2", "samparray3", "samparray4")
ExprmL+     ))

ExprmL> ## Create a mock RangedSummarizedExperiment from a data.frame
ExprmL> rangedat <- data.frame(chr="chr2", start = 11:15, end = 12:16,
ExprmL+     strand = c("+", "-", "+", "*", "."),
ExprmL+     samp0 = c(0,0,1,1,1), samp1 = c(1,0,1,0,1), samp2 = c(0,1,0,1,0),
ExprmL+     row.names = paste0("GENE", letters[5:1]))

ExprmL> rangeSE <- SummarizedExperiment::makeSummarizedExperimentFromDataFrame(rangedat)

ExprmL> ## Combine to a named list and call the ExperimentList constructor function
ExprmL> assayList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

ExprmL> ## Use the ExperimentList constructor
ExprmL> ExpList <- ExperimentList(assayList)

MltAsE> ## Create sample maps for each experiment
MltAsE> exprmap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("array1", "array2", "array3", "array4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> methylmap <- data.frame(
MltAsE+     primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
MltAsE+     colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> rnamap <- data.frame(
MltAsE+     primary = c("Jack", "Jill", "Bob", "Barbara"),
MltAsE+     colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> gistmap <- data.frame(
MltAsE+     primary = c("Jack", "Bob", "Jill"),
MltAsE+     colname = c("samp0", "samp1", "samp2"),
MltAsE+     stringsAsFactors = FALSE)

MltAsE> ## Combine as a named list and convert to a DataFrame
MltAsE> maplist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> sampMap <- listToMap(maplist)

MltAsE> ## Create an example phenotype data
MltAsE> colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
MltAsE+     row.names = c("Jack", "Jill", "Bob", "Barbara"))

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
MltAsE+     sampleMap = sampMap)
══ testthat results  ═══════════════════════════════════════════════════════════
OK: 143 SKIPPED: 0 FAILED: 0
> 
> proc.time()
   user  system elapsed 
 27.300   0.340  28.075

Example timings

MultiAssayExperiment.Rcheck/MultiAssayExperiment-Ex.timings

nameusersystemelapsed
ExperimentList-class0.0320.0000.032
ExperimentList0.3080.0000.311
MatchedAssayExperiment-class0.7000.0320.732
MultiAssayExperiment-class2.6480.0402.832
MultiAssayExperiment-methods0.3200.0040.324
MultiAssayExperiment0.2920.0000.294
hasAssay0.0080.0000.008
mapToList0.3480.0040.352
miniACC1.5680.0081.581
prepMultiAssay0.7680.0040.773
reexports0.0040.0000.002
subsetBy1.9640.0081.975
upsetSamples1.8640.0201.889