Differentially expression analysis (DEA) using edgeR package.
TCGAanalyze_DEA allows user to perform Differentially expression analysis (DEA), using edgeR package to identify differentially expressed genes (DEGs). It is possible to do a two-class analysis.
TCGAanalyze_DEA performs DEA using following functions from edgeR:
- edgeR::DGEList converts the count matrix into an edgeR object.
- edgeR::estimateCommonDisp each gene gets assigned the same dispersion estimate.
- edgeR::exactTest performs pair-wise tests for differential expression between two groups.
- edgeR::topTags takes the output from exactTest(), adjusts the raw p-values using the False Discovery Rate (FDR) correction, and returns the top differentially expressed genes.
TCGAanalyze_DEA(mat1, mat2, Cond1type, Cond2type, method = "exactTest", fdr.cut = 1, logFC.cut = 0, elementsRatio = 30000)
- numeric matrix, each row represents a gene, each column represents a sample with Cond1type
- numeric matrix, each row represents a gene, each column represents a sample with Cond2type
- a string containing the class label of the samples in mat1 (e.g., control group)
- a string containing the class label of the samples in mat2 (e.g., case group)
- is 'glmLRT' (1) or 'exactTest' (2). (1) Fit a negative binomial generalized log-linear model to the read counts for each gene (2) Compute genewise exact tests for differences in the means between two groups of negative-binomially distributed counts.
- is a threshold to filter DEGs according their p-value corrected
- is a threshold to filter DEGs according their logFC
- is number of elements processed for second for time consumation estimation
table with DEGs containing for each gene logFC, logCPM, pValue,and FDR
dataNorm <- TCGAbiolinks::TCGAanalyze_Normalization(dataBRCA, geneInfo) dataFilt <- TCGAanalyze_Filtering(tabDF = dataBRCA, method = "quantile", qnt.cut = 0.25) samplesNT <- TCGAquery_SampleTypes(colnames(dataFilt), typesample = c("NT")) samplesTP <- TCGAquery_SampleTypes(colnames(dataFilt), typesample = c("TP")) dataDEGs <- TCGAanalyze_DEA(dataFilt[,samplesNT], dataFilt[,samplesTP],"Normal", "Tumor")