panev.network.enrichment: Enrichment analysis considering PANEV result as a background

In vpalombo/PANEV: PaNeV: an R package for a pathway-based network visualization

Enrichment analysis considering PANEV result as a background

Description

The function perform an enrichment analysis considering as backgroud the union of pathways investigated by PANEV for generate network result.The result help to interpret the PANEV output allowing to identify the pathways most strongly associated with the input list of genes.

Usage

panev.network.enrichment(in.file, out.file = "PANEV_enrich", species = NULL, FL = NULL, levels = 2)

Arguments

in.file	Name of input file (with extension) containing the gene list of interest. The file must contain three columns labelled as 'ensembl_gene_id', 'entrezgene' and 'external_gene_name', respectively. The file must rely in the working directory. The handy function panev.dataPreparation could be used to create a properly formatted input file from a single gene list.
out.file	Name of the folder where the results will be stored and of the output diagram file (default = 'PANEV_enrich').
species	The code of your species of interest. The correct code can get among the list of those available in KEGG with the handy function panev.speciesCode.
FL	A list of pathways of first level to investigate. The list of all available pathways can get with the panev.pathList function.
levels	The number of levels of interactions (from 1 to n) investingated (default = 2).

Details

This function is based on keggList and keggLink functions of KEGGREST package (http://bioconductor.org/packages/release/bioc/html/KEGGREST.html.

The enrichment analysis is based on enrichment function of bc3net package (https://cran.r-project.org/web/packages/bc3net/index.html.

Value

A <out.file>_enrichment.txt file containing the results of functional enrichment analysis, based on a one-sided Fisher's exact test (hypergeometric test) and considering the PANEV network as a background.

Author(s)

Valentino Palombo ([e-mail])

References

Tenenbaum D (2017). KEGGREST: Client-side REST access to KEGG. R package version 1.16.1.

Simoes R de M, Emmert-Streib F (2012). Bagging statistical network inference from large-scale gene expression data. PLOS ONE; 7: e33624. doi:10.1371/journal.pone.0033624

Examples

##### EXAMPLES CODE #####
#Copy the example files in the current working directory
panev.example()

#Look for the organism code matching the search string 
list <- panev.biomartSpecies(string = "cow")
biomart.species <- as.character(list[1,1]) # btaurus_gene_ensembl

#Prepare PANEV input file using a gene list containing ensembl gene id.
genelist_converted <- panev.dataPreparation(in.file = "ensembl_genelist.txt", 
                                          gene_id = "ensembl", 
                                          biomart.species = biomart.species)

#Look for the specie code matching the search string 
list <- panev.speciesCode(string = "bos")
species <- as.character(list[1,2]) # bta

#Overview on input data 
panev.network.enrichment(in.file = in.file, 
              out.file = out.file, 
              species = species, 
              FL = FL, 
              levels = 3)

vpalombo/PANEV documentation built on June 13, 2022, 1:11 p.m.