Package: MultiAssayExperiment

Version: 1.4.9

Command: /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --no-vignettes --timings MultiAssayExperiment_1.4.9.tar.gz

StartedAt: 2018-04-12 06:52:18 -0400 (Thu, 12 Apr 2018)

EndedAt: 2018-04-12 06:55:17 -0400 (Thu, 12 Apr 2018)

EllapsedTime: 179.3 seconds

RetCode: 0

Status:  OK

CheckDir: MultiAssayExperiment.Rcheck

Warnings: 0

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### Running command:
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###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --no-vignettes --timings MultiAssayExperiment_1.4.9.tar.gz
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* using log directory ‘/Users/biocbuild/bbs-3.6-bioc/meat/MultiAssayExperiment.Rcheck’
* using R version 3.4.4 (2018-03-15)
* using platform: x86_64-apple-darwin15.6.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘MultiAssayExperiment/DESCRIPTION’ ... OK
* this is package ‘MultiAssayExperiment’ version ‘1.4.9’
* 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 object imported by a ':::' call: ‘BiocGenerics:::replaceSlots’
  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 sizes of PDF files under ‘inst/doc’ ... OK
* checking installed files from ‘inst/doc’ ... 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
  ‘/Users/biocbuild/bbs-3.6-bioc/meat/MultiAssayExperiment.Rcheck/00check.log’
for details.

* installing *source* package ‘MultiAssayExperiment’ ...
** R
** data
*** moving datasets to lazyload DB
** inst
** preparing package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (MultiAssayExperiment)

R version 3.4.4 (2018-03-15) -- "Someone to Lean On"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (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> arraypdat <- as(data.frame(
ExprmL+     slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4")),
ExprmL+     "AnnotatedDataFrame")

ExprmL> ## ExpressionSet constructor
ExprmL> exprdat <- Biobase::ExpressionSet(assayData = arraydat, phenoData = arraypdat)

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

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",
MltAsE+                                "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

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

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

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

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+                                                colData = colDat,
MltAsE+                                                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> arraypdat <- as(data.frame(
ExprmL+     slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4")),
ExprmL+     "AnnotatedDataFrame")

ExprmL> ## ExpressionSet constructor
ExprmL> exprdat <- Biobase::ExpressionSet(assayData = arraydat, phenoData = arraypdat)

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

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",
MltAsE+                                "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

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

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

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

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+                                                colData = colDat,
MltAsE+                                                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> arraypdat <- as(data.frame(
ExprmL+     slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4")),
ExprmL+     "AnnotatedDataFrame")

ExprmL> ## ExpressionSet constructor
ExprmL> exprdat <- Biobase::ExpressionSet(assayData = arraydat, phenoData = arraypdat)

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

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",
MltAsE+                                "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

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

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

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

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+                                                colData = colDat,
MltAsE+                                                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> arraypdat <- as(data.frame(
ExprmL+     slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4")),
ExprmL+     "AnnotatedDataFrame")

ExprmL> ## ExpressionSet constructor
ExprmL> exprdat <- Biobase::ExpressionSet(assayData = arraydat, phenoData = arraypdat)

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

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",
MltAsE+                                "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

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

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

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

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+                                                colData = colDat,
MltAsE+                                                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> arraypdat <- as(data.frame(
ExprmL+     slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4")),
ExprmL+     "AnnotatedDataFrame")

ExprmL> ## ExpressionSet constructor
ExprmL> exprdat <- Biobase::ExpressionSet(assayData = arraydat, phenoData = arraypdat)

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

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",
MltAsE+                                "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

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

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

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

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+                                                colData = colDat,
MltAsE+                                                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> arraypdat <- as(data.frame(
ExprmL+     slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4")),
ExprmL+     "AnnotatedDataFrame")

ExprmL> ## ExpressionSet constructor
ExprmL> exprdat <- Biobase::ExpressionSet(assayData = arraydat, phenoData = arraypdat)

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

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",
MltAsE+                                "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

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

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

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

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+                                                colData = colDat,
MltAsE+                                                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> arraypdat <- as(data.frame(
ExprmL+     slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4")),
ExprmL+     "AnnotatedDataFrame")

ExprmL> ## ExpressionSet constructor
ExprmL> exprdat <- Biobase::ExpressionSet(assayData = arraydat, phenoData = arraypdat)

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

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",
MltAsE+                                "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

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

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

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

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+                                                colData = colDat,
MltAsE+                                                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> arraypdat <- as(data.frame(
ExprmL+     slope53 = rnorm(4),
ExprmL+     row.names = c("array1", "array2", "array3", "array4")),
ExprmL+     "AnnotatedDataFrame")

ExprmL> ## ExpressionSet constructor
ExprmL> exprdat <- Biobase::ExpressionSet(assayData = arraydat, phenoData = arraypdat)

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

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",
MltAsE+                                "samparray4"),
MltAsE+     stringsAsFactors = FALSE)

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

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

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

MltAsE> ## Create a MultiAssayExperiment instance
MltAsE> myMultiAssayExperiment <- MultiAssayExperiment(experiments = ExpList,
MltAsE+                                                colData = colDat,
MltAsE+                                                sampleMap = mySampleMap)
══ testthat results  ═══════════════════════════════════════════════════════════
OK: 112 SKIPPED: 0 FAILED: 0
> 
> proc.time()
   user  system elapsed 
 21.043   0.315  21.748 

name	user	system	elapsed
API	0.001	0.000	0.000
ExperimentList-class	0.017	0.001	0.021
ExperimentList	0.212	0.003	0.215
MatchedAssayExperiment-class	1.324	0.033	1.373
MultiAssayExperiment-class	2.366	0.012	2.410
MultiAssayExperiment-methods	0.240	0.003	0.247
MultiAssayExperiment	0.179	0.002	0.182
clusterOn	0.655	0.004	0.670
hasAssay	0.006	0.000	0.006
mapToList	0.229	0.003	0.242
miniACC	1.032	0.005	1.056
prepMultiAssay	0.466	0.003	0.475
subsetBy	2.002	0.008	2.055
upsetSamples	2.583	0.045	2.668