performDifferentialExpression: Perform differential gene expression based on ENCODE data

In nuno-agostinho/cTRAP: Identification of candidate causal perturbations from differential gene expression data

Perform differential gene expression based on ENCODE data

Description

Perform differential gene expression based on ENCODE data

Usage

performDifferentialExpression(counts)

Arguments

counts

Data frame: gene expression

Value

Data frame with differential gene expression results between knockdown and control

See Also

Other functions related with using ENCODE expression data: downloadENCODEknockdownMetadata(), loadENCODEsamples(), prepareENCODEgeneExpression()

Examples

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)
}

nuno-agostinho/cTRAP documentation built on March 28, 2024, 3:59 p.m.