TCGAanalyze_LevelTab: Adding information related to DEGs genes from DEA as mean...

In TCGAbiolinks: TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data

Description

TCGAanalyze_LevelTab allows user to add information related to DEGs genes from Differentially expression analysis (DEA) such as mean values and in two conditions.

Usage

TCGAanalyze_LevelTab(
  FC_FDR_table_mRNA,
  typeCond1,
  typeCond2,
  TableCond1,
  TableCond2,
  typeOrder = TRUE
)

Arguments

FC_FDR_table_mRNA	Output of dataDEGs filter by abs(LogFC) >=1
typeCond1	a string containing the class label of the samples in TableCond1 (e.g., control group)
typeCond2	a string containing the class label of the samples in TableCond2 (e.g., case group)
TableCond1	numeric matrix, each row represents a gene, each column represents a sample with Cond1type
TableCond2	numeric matrix, each row represents a gene, each column represents a sample with Cond2type
typeOrder	typeOrder

Value

table with DEGs, log Fold Change (FC), false discovery rate (FDR), the gene expression level for samples in Cond1type, and Cond2type, and Delta value (the difference of gene expression between the two conditions multiplied logFC)

Examples

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],
                            Cond1type = "Normal",
                            Cond2type = "Tumor")
dataDEGsFilt <- dataDEGs[abs(dataDEGs$logFC) >= 1,]
dataTP <- dataFilt[,samplesTP]
dataTN <- dataFilt[,samplesNT]
dataDEGsFiltLevel <- TCGAanalyze_LevelTab(dataDEGsFilt,"Tumor","Normal",
dataTP,dataTN)

TCGAbiolinks documentation built on Nov. 8, 2020, 5:37 p.m.