performDifferentialExpression {cTRAP} | R Documentation |
Perform differential gene expression based on ENCODE data
performDifferentialExpression(counts)
counts |
Data frame: gene expression |
Data frame with differential gene expression results between knockdown and control
Other functions related with using ENCODE expression data:
downloadENCODEknockdownMetadata()
,
loadENCODEsamples()
,
prepareENCODEgeneExpression()
if (interactive()) { # Download ENCODE metadata for a specific cell line and gene cellLine <- "HepG2" gene <- "EIF4G1" ENCODEmetadata <- downloadENCODEknockdownMetadata(cellLine, gene) # Download samples based on filtered ENCODE metadata ENCODEsamples <- loadENCODEsamples(ENCODEmetadata)[[1]] counts <- prepareENCODEgeneExpression(ENCODEsamples) # Remove low coverage (at least 10 counts shared across two samples) minReads <- 10 minSamples <- 2 filter <- rowSums(counts[ , -c(1, 2)] >= minReads) >= minSamples counts <- counts[filter, ] # Convert ENSEMBL identifier to gene symbol counts$gene_id <- convertGeneIdentifiers(counts$gene_id) # Perform differential gene expression analysis diffExpr <- performDifferentialExpression(counts) }