GSEA_run: Function to run a GSEA analysis

In LauraPS1/TFEA.ChIP: Analyze Transcription Factor Enrichment

Function to run a GSEA analysis

Description

Function to run a GSEA to analyze the distribution of TFBS across a sorted list of genes.

Usage

GSEA_run(
  gene.list,
  LFC,
  chip_index = get_chip_index(),
  get.RES = FALSE,
  RES.filter = NULL,
  perms = 1000
)

Arguments

gene.list	List of Entrez IDs ordered by their fold change.
LFC	Vector of log2( Fold Change ) values.
chip_index	Output of the function “get_chip_index”, a data frame containing accession IDs of ChIPs on the database and the TF each one tests. If not provided, the whole internal database will be used
get.RES	(Optional) boolean. If TRUE, the function stores Running Enrichment Scores of all/some TF.
RES.filter	(Optional) chr vector. When get.RES==TRUE, allows to choose which TF's Running Enrichment Score to store.
perms	(Optional) integer. Number of permutations for the enrichment test.

Value

a list of: Enrichment.table: data frame containing accession ID, Cell type, ChIP-Seq treatment, transcription factor tested, enrichment score, adjusted p-value, and argument of every ChIP-Seq experiment. RES (optional): list of running sums of every ChIP-Seq indicators (optional): list of 0/1 vectors that stores the matches (1) and mismatches (0) between the gene list and the gene set.

Examples

data( 'hypoxia', package = 'TFEA.ChIP' )
hypoxia <- preprocessInputData( hypoxia )
chip_index <- get_chip_index( TFfilter = c('HIF1A','EPAS1','ARNT' ) )
GSEA.result <- GSEA_run( hypoxia$Genes, hypoxia$log2FoldChange, chip_index, get.RES = TRUE)

LauraPS1/TFEA.ChIP documentation built on April 21, 2023, 7:29 a.m.