funcEnrich.Fisher: Gene Set Enrichment Analysis by Fisher's Exact Test

In jyyulab/NetBID: Network-based Bayesian Inference of Drivers, version 2

Gene Set Enrichment Analysis by Fisher's Exact Test

Description

funcEnrich.Fisher performs gene set enrichment analysis to the input gene list, by using the Fisher's Exact Test. Background gene list is accepeted.

Usage

funcEnrich.Fisher(
  input_list = NULL,
  bg_list = NULL,
  use_gs = NULL,
  gs2gene = NULL,
  min_gs_size = 5,
  max_gs_size = 500,
  Pv_adj = "fdr",
  Pv_thre = 0.1
)

Arguments

input_list	a vector of characters, a vector of gene symbols. If gene symbols are not available, users can call get_IDtransfer and get_name_transfertab for ID conversion.
bg_list	a vector of characters, a vector of background gene symbols. If NULL, genes in gs2gene will be used as background. Default is NULL.
use_gs	a vector of characters, the names of gene sets. If gs2gene is NULL, all_gs2gene will be used. The use_gs must be the subset of names(all_gs2gene). If "all", all the gene sets in gs2gene will be used. If user input his own gs2gene list, use_gs will be set to "all" as default. Default is c("H", "CP:BIOCARTA", "CP:REACTOME", "CP:KEGG").
gs2gene	list, a list contains elements of gene sets. The name of the element is gene set, each element contains a vector of genes in that gene set. If NULL, will use all_gs2gene, which is created by function gs.preload. Default is NULL.
min_gs_size	numeric, the minimum size of gene set to analysis. Default is 5.
max_gs_size	numeric, the maximum size of gene set to analysis. Default is 500.
Pv_adj	character, method to adjust P-value. Default is "fdr". For details, please check p.adjust.methods.
Pv_thre	numeric, threshold for the adjusted P-values. Default is 0.1.

Value

Return a data.frame, contains gene sets with significant enrichment statistics. Column details are as follows,

#Name	Name of the enriched gene set
Total_item	Background size
Num_item	Number of genes in the gene set (filtered by the background list)
Num_list	Number of input genes for testing (filtered by the background list)
Num_list_item	Number of input genes annotated by the gene set (filtered by the background list)
Ori_P	Original P-value from Fisher's Exact Test
Adj_P	Adjusted P-value
Odds_Ratio	Odds ratio from the 2*2 matrix used for Fisher's Exact Test
Intersected_items	A vector of the intersected genes, collapsed by ';'. Number is equal to Num_list_item

Examples

analysis.par <- list()
analysis.par$out.dir.DATA <- system.file('demo1','driver/DATA/',package = "NetBID2")
NetBID.loadRData(analysis.par=analysis.par,step='ms-tab')
ms_tab <- analysis.par$final_ms_tab
sig_driver <- draw.volcanoPlot(dat=ms_tab,label_col='gene_label',
                               logFC_col='logFC.G4.Vs.others_DA',
                               Pv_col='P.Value.G4.Vs.others_DA',
                               logFC_thre=0.4,
                               Pv_thre=1e-7,
                               main='Volcano Plot for G4.Vs.others_DA',
                               show_label=FALSE,
                               label_type = 'origin',
                               label_cex = 0.5)
gs.preload(use_spe='Homo sapiens',update=FALSE)
res1 <- funcEnrich.Fisher(input_list=ms_tab[rownames(sig_driver),'geneSymbol'],
                               bg_list=ms_tab[,'geneSymbol'],
                               use_gs=c('H','C5'),
                               Pv_thre=0.1,Pv_adj = 'none')
## Not run: 

jyyulab/NetBID documentation built on Dec. 23, 2024, 6:34 a.m.