pip.norm.DE: Pipeline of Differential Expression Analysis for RNASeq Data
In LXQin/PRECISION.seq: Comparison of Depth Normalization Methods

Description Usage Arguments Value Examples

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
)

`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

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.