Pipeline of Differential Expression Analysis for RNASeq Data

This is a pipeline function performing the DEA starting from the data normalization. Users can select the normalization method and DE method by themselves.

pip.norm.DE(
  raw,
  groups,
  norm.method,
  QN_filter = FALSE,
  DE.method = "DE.voom",
  Pval = 0.01
)

Arguments

raw	raw count data in the format of data frame or matrix, with columns for samples and raws for genes.
groups	vector of characters indicating the group for each sample (only 2 groups allowed).
norm.method	the method for normalization selected from all norm.none, norm.TMM, norm.TC, norm.UQ, norm.med, norm.DESeq, norm.PoissonSeq, norm.QN, norm.SVA, norm.RUVr, norm.RUVg, and norm.RUVs. The function applies all available normalization methods if all is selected.
QN_filter	whether the filtering is performed if method = norm.QN.
DE.method	the method for differential expression analysis from DE.voom and DE.edgeR, default to be DE.voom.
Pval	p-value for identifying DE genes, default to be 0.01

Value

list, containing id.list (names of DE genes), p.val, and log2.FC for a single normalization. If method="all", a list of of DEAs is returned for the raw data normalized with each supported normaliztion methods vontaining containing id.list (names of DE genes), p.val, and log2.FC each.

Examples

res <- pip.norm.DE(data.test, data.group, "norm.TMM")