Integrate Two Differential Expression Results.

Integrate Two Differential Expression Results.

DEbDE(
  de1.res,
  de2.res,
  de1.signif = "padj",
  de1.signif.threshold = 0.05,
  de1.l2fc.threshold = 1,
  de2.signif = "padj",
  de2.signif.threshold = 0.05,
  de2.l2fc.threshold = 1
)

Arguments

de1.res

DE1 dataframe contains all genes of differential expression analysis.
de2.res

DE2 dataframe contains all genes of differential expression analysis.
de1.signif

Significance criterion for DE1. For DESeq2 results, can be chosen from padj, pvalue. For edgeR results, can be chosen from FDR, PValue. Default: padj.
de1.signif.threshold

Significance threshold for DE1 to get differentially expressed genes. Default: 0.05.
de1.l2fc.threshold

Log2 fold change threshold for DE1 to get differentially expressed genes. Default: 1.
de2.signif

Significance criterion for DE2. For DESeq2 results, can be chosen from padj, pvalue. For edgeR results, can be chosen from FDR, PValue. Default: padj.
de2.signif.threshold

Significance threshold for DE2 to get differentially expressed genes. Default: 0.05.
de2.l2fc.threshold

Log2 fold change threshold for DE2 to get differentially expressed genes. Default: 1.

Value

Dataframe contains integration results, the 'Type' column contains "Down_Up", "Up_Up", "Down_Down", "Up_Down", "DE1_Up", "DE1_Down", "DE2_Up", "DE2_Down", "Not_Not".

Examples

library(DEbPeak)
rna.diff.file <- system.file("extdata", "RA_RNA_diff.txt", package = "DEbPeak")
de1.res <- read.table(file = rna.diff.file, header = TRUE, sep = "\t")
de2.res <- read.table(file = rna.diff.file, header = TRUE, sep = "\t")
# use same file as example
de.de <- DEbDE(de1.res = de1.res, de2.res = de2.res, de1.l2fc.threshold = 0.5, de2.l2fc.threshold = 1)

#> Differential expression analysis with DESeq2!
#> Differential expression analysis with DESeq2!