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> 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, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
pmin.int, rank, rbind, rownames, sapply, 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
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, rowsum
>
> example("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 = c(paste0("ENST", "00000", 135411:135414), "ENST00000383323"))
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)
>
> test_check("MultiAssayExperiment")
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 183 | SKIPPED: 0 | WARNINGS: 8 | FAILED: 0 ]
>
> proc.time()
user system elapsed
41.228 1.181 42.537