MultiAssayExperiment {MultiAssayExperiment} | R Documentation |
MultiAssayExperiment
The constructor function for the MultiAssayExperiment-class combines
multiple data elements from the different hierarchies of data
(study, experiments, and samples). It can create instances where neither
a sampleMap
or a colData
set is provided. Please see the
MultiAssayExperiment API documentation for more information.
MultiAssayExperiment( experiments = ExperimentList(), colData = S4Vectors::DataFrame(), sampleMap = S4Vectors::DataFrame(assay = factor(), primary = character(), colname = character()), metadata = list(), drops = list() )
experiments |
A |
colData |
A |
sampleMap |
A |
metadata |
An optional argument of "ANY" class (usually list) for content describing the experiments |
drops |
A |
A MultiAssayExperiment
object that can store
experiment and phenotype data
## Run the example ExperimentList example("ExperimentList") ## Create sample maps for each experiment exprmap <- data.frame( primary = c("Jack", "Jill", "Barbara", "Bob"), colname = c("array1", "array2", "array3", "array4"), stringsAsFactors = FALSE) methylmap <- data.frame( primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"), colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"), stringsAsFactors = FALSE) rnamap <- data.frame( primary = c("Jack", "Jill", "Bob", "Barbara"), colname = c("samparray1", "samparray2", "samparray3", "samparray4"), stringsAsFactors = FALSE) gistmap <- data.frame( primary = c("Jack", "Bob", "Jill"), colname = c("samp0", "samp1", "samp2"), stringsAsFactors = FALSE) ## Combine as a named list and convert to a DataFrame maplist <- list(Affy = exprmap, Methyl450k = methylmap, RNASeqGene = rnamap, GISTIC = gistmap) ## Create a sampleMap sampMap <- listToMap(maplist) ## Create an example phenotype data colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41, row.names = c("Jack", "Jill", "Bob", "Barbara")) ## Create a MultiAssayExperiment instance mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat, sampleMap = sampMap)