| Environment | Status |
|---|---|
| BioC-release |  |
| BioC-devel |  |
The alabaster.mae package implements methods for saving and loading MultiAssayExperiment objects under the alabaster framework. It provides a language-agnostic method for serializing the sample mappings, sample data, and the various SummarizedExperiment instances nested within the MAE. To get started, install the package and its dependencies from Bioconductor:
# install.packages("BiocManager")BiocManager::install("alabaster.mae")To demonstrate, let's create a mildly complicated MAE containing RNA-seq and ChIP-seq data with partial overlaps:
library(SummarizedExperiment) rna.counts<-matrix(rpois(60, 10), ncol=6) colnames(rna.counts) <- c("disease1", "disease2", "disease3", "control1", "control2", "control3") rownames(rna.counts) <- c("ENSMUSG00000000001", "ENSMUSG00000000003", "ENSMUSG00000000028", "ENSMUSG00000000031", "ENSMUSG00000000037", "ENSMUSG00000000049", "ENSMUSG00000000056", "ENSMUSG00000000058", "ENSMUSG00000000078", "ENSMUSG00000000085") rna.se<- SummarizedExperiment(list(counts=rna.counts)) colData(rna.se)$disease<- rep(c("disease", "control"), each=3) chip.counts<-matrix(rpois(100, 10), ncol=4) colnames(chip.counts) <- c("disease1", "disease2", "control1", "control3") chip.peaks<- GRanges("chr1", IRanges(1:25*100+1, 1:25*100+100)) chip.se<- SummarizedExperiment(list(counts=chip.counts), rowRanges=chip.peaks) library(MultiAssayExperiment) mapping<- DataFrame( primary= c(colnames(rna.se), colnames(chip.se)), # sample identifiersassay= rep(c("rnaseq", "chipseq"), c(ncol(rna.se), ncol(chip.se))), # experiment namecolname= c(colnames(rna.se), colnames(chip.se)) # column names inside each experiment ) mae<- MultiAssayExperiment(list(rnaseq=rna.se, chipseq=chip.se), sampleMap=mapping)Now we can just save it to file:
library(alabaster.mae) tmp<- tempfile() saveObject(mae, tmp)And easily load it back:
roundtrip<- readObject(tmp) roundtrip## A MultiAssayExperiment object of 2 listed## experiments with user-defined names and respective classes.## Containing an ExperimentList class object of length 2:## [1] rnaseq: SummarizedExperiment with 10 rows and 6 columns## [2] chipseq: RangedSummarizedExperiment with 25 rows and 4 columns## Functionality:## experiments() - obtain the ExperimentList instance## colData() - the primary/phenotype DataFrame## sampleMap() - the sample coordination DataFrame## `$`, `[`, `[[` - extract colData columns, subset, or experiment## *Format() - convert into a long or wide DataFrame## assays() - convert ExperimentList to a SimpleList of matrices## exportClass() - save data to flat files