TF_Selection: Identifying enriched TFs using Gene Set Enrichment Analysis...

In lusystemsbio/NetAct: NetAct -- a computational platform to construct core transcription factor regulatory networks using gene activity

Identifying enriched TFs using Gene Set Enrichment Analysis (GSEA) – a wrapper function with many options

Description

Identifying enriched TFs using Gene Set Enrichment Analysis (GSEA) – a wrapper function with many options

Usage

TF_Selection(
  GSDB,
  DErslt,
  minSize = 5,
  nperm = 5000,
  method = "binary",
  qval = 0.05,
  compList = NULL,
  ntop = NULL,
  nameFile = NULL
)

Arguments

GSDB	gene set database (a list of gene sets, each of which is comprised of a vector genes)
DErslt	DEG results
minSize	the minimum number of overlapping genes required for each gene set (a gene set filtering parameter, default: 5)
nperm	the number of gene list permutations (default: 1000)
method	fast: fgsea; R: r implementation of GSEA with a new permutation method; binary: R/C++ implementation for fast speed
qval	q-value cutoff (default: 0.05)
compList	a vector of comparisons, it needs to be consistent with DErslt from MicroDegs, RNAseqDegs_limma, and RNAseqDegs_DESeq. GSEA is applied to each comparison
ntop	the number of top genes (selection by the top genes) (default: NULL, no selection by the top genes)
nameFile	file name to save the GSEA results (default: NULL, no output to a file). The saved results can be reused later to adjust the TF selection parameters

Value

a list of results: GSEArslt: a dataframe of GSEA results (see TF_GSEA). tfs: a vector of selected TFs.

lusystemsbio/NetAct documentation built on Sept. 7, 2024, 8:34 p.m.