Back to Multiple platform build/check report for BioC 3.7
ABCDEFGHIJKL[M]NOPQRSTUVWXYZ

CHECK report for MultiAssayExperiment on malbec2

This page was generated on 2018-10-17 08:28:46 -0400 (Wed, 17 Oct 2018).

Package 961/1561HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
MultiAssayExperiment 1.6.0
Marcel Ramos
Snapshot Date: 2018-10-15 16:45:08 -0400 (Mon, 15 Oct 2018)
URL: https://git.bioconductor.org/packages/MultiAssayExperiment
Branch: RELEASE_3_7
Last Commit: 40c8a32
Last Changed Date: 2018-04-30 10:35:41 -0400 (Mon, 30 Apr 2018)
malbec2 Linux (Ubuntu 16.04.1 LTS) / x86_64  OK  OK [ OK ]UNNEEDED, same version exists in internal repository
tokay2 Windows Server 2012 R2 Standard / x64  OK  OK  OK  OK UNNEEDED, same version exists in internal repository
merida2 OS X 10.11.6 El Capitan / x86_64  OK  OK  OK  OK UNNEEDED, same version exists in internal repository

Summary

Package: MultiAssayExperiment
Version: 1.6.0
Command: /home/biocbuild/bbs-3.7-bioc/R/bin/R CMD check --install=check:MultiAssayExperiment.install-out.txt --library=/home/biocbuild/bbs-3.7-bioc/R/library --no-vignettes --timings MultiAssayExperiment_1.6.0.tar.gz
StartedAt: 2018-10-16 02:14:46 -0400 (Tue, 16 Oct 2018)
EndedAt: 2018-10-16 02:16:59 -0400 (Tue, 16 Oct 2018)
EllapsedTime: 133.8 seconds
RetCode: 0
Status:  OK 
CheckDir: MultiAssayExperiment.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.7-bioc/R/bin/R CMD check --install=check:MultiAssayExperiment.install-out.txt --library=/home/biocbuild/bbs-3.7-bioc/R/library --no-vignettes --timings MultiAssayExperiment_1.6.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.7-bioc/meat/MultiAssayExperiment.Rcheck’
* using R version 3.5.1 Patched (2018-07-12 r74967)
* 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 ‘1.6.0’
* 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 ‘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-3.7-bioc/meat/MultiAssayExperiment.Rcheck/00check.log’
for details.

Installation output

MultiAssayExperiment.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.7-bioc/R/bin/R CMD INSTALL MultiAssayExperiment
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.7-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 3.5.1 Patched (2018-07-12 r74967) -- "Feather Spray"
Copyright (C) 2018 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)
> 
> 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> ExpList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

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

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> mylist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> mySampleMap <- listToMap(mylist)

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> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+     colData = colDat, sampleMap = mySampleMap)

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> ExpList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

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

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> mylist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> mySampleMap <- listToMap(mylist)

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> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+     colData = colDat, sampleMap = mySampleMap)

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> ExpList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

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

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> mylist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> mySampleMap <- listToMap(mylist)

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> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+     colData = colDat, sampleMap = mySampleMap)

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> ExpList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

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

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> mylist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> mySampleMap <- listToMap(mylist)

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> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+     colData = colDat, sampleMap = mySampleMap)

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> ExpList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

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

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> mylist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> mySampleMap <- listToMap(mylist)

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> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+     colData = colDat, sampleMap = mySampleMap)

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> ExpList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

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

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> mylist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> mySampleMap <- listToMap(mylist)

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> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+     colData = colDat, sampleMap = mySampleMap)

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> ExpList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

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

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> mylist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> mySampleMap <- listToMap(mylist)

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> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+     colData = colDat, sampleMap = mySampleMap)

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> ExpList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
ExprmL+                 GISTIC = rangeSE)

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

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> mylist <- list(Affy = exprmap, Methyl450k = methylmap,
MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)

MltAsE> ## Create a sampleMap
MltAsE> mySampleMap <- listToMap(mylist)

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> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+     colData = colDat, sampleMap = mySampleMap)
══ testthat results  ═══════════════════════════════════════════════════════════
OK: 124 SKIPPED: 0 FAILED: 0
> 
> proc.time()
   user  system elapsed 
 18.420   0.336  18.954

Example timings

MultiAssayExperiment.Rcheck/MultiAssayExperiment-Ex.timings

nameusersystemelapsed
ExperimentList-class0.020.000.02
ExperimentList0.2080.0000.210
MatchedAssayExperiment-class0.6040.0080.610
MultiAssayExperiment-class2.2440.0322.293
MultiAssayExperiment-methods0.1960.0000.196
MultiAssayExperiment0.1680.0040.172
hasAssay0.0040.0000.004
mapToList0.2040.0000.208
miniACC0.9080.0000.907
prepMultiAssay0.4080.0000.410
reexports0.0040.0000.001
subsetBy2.0440.0002.047
upsetSamples1.0840.0161.104