TCGAanalyze_LevelTab {TCGAbiolinks} | R Documentation

## Adding information related to DEGs genes from DEA as mean values in two conditions.

### 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)

[Package TCGAbiolinks version 2.8.4 Index]