R/panev.network.enrichment.R
In vpalombo/PANEV: PaNeV: an R package for a pathway-based network visualization
Defines functions
panev.network.enrichment
Documented in
panev.network.enrichment
#' @title Enrichment analysis considering PANEV result as a background
#' @description The function perform an enrichment analysis of the genes highlighted by PANEV using the union of pathways investigated for generating the network result as a background.The result help to interpret the PANEV output and allows identifying the pathways most strongly associated with the generated gene list.
#' @usage panev.network.enrichment(in.file, out.file = "PANEV_enrich", species = NULL, FL = NULL, levels = 2)
#' @param in.file Name of input file (with extension) containing the gene list of interest. The file \bold{must} contain three columns labelled as \emph{'ensembl_gene_id'}, \emph{'entrezgene'} and \emph{'external_gene_name'}, respectively. The file \bold{must} rely in the working directory. The handy function \code{\link[PANEV]{panev.dataPreparation}} could be used to create a properly formatted input file from a single gene list.
#' @param out.file Name of the folder where the results will be stored and of the output diagram file (default = 'PANEV_enrich').
#' @param 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 \code{\link[PANEV]{panev.speciesCode}}.
#' @param FL A list of pathways of first level to investigate. The list of all available pathways can get with the \code{\link[PANEV]{panev.pathList}} function.
#' @param levels The number of levels of interactions (from \emph{1} to \emph{n}) investingated (default = 2).
#' @details This function is based on \code{\link[KEGGREST]{keggList}} and \code{\link[KEGGREST]{keggLink}} functions of \pkg{KEGGREST} package (\url{http://bioconductor.org/packages/release/bioc/html/KEGGREST.html}.
#' @details The enrichment analysis is based on \code{\link[bc3net]{enrichment}} function of \pkg{bc3net} package (\url{https://cran.r-project.org/web/packages/bc3net/index.html}.
#' @return A \emph{<out.file>_net.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 Valentino Palombo (\email{valentino.palombo@gmail.com})
#' @references Tenenbaum D (2017). KEGGREST: Client-side REST access to KEGG. R package version 1.16.1.
#' @references 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
#'
#' #Specify the first level pathways to investigate
#' FL = c("path:map00061", "path:map00062", "path:map00071", "path:map00072")
#' #Specify the number of levels of pathways to investigate
#' levels = 3
#'
#' #Run the PANEV enrichment function
#' panev.network.enrichment(in.file = "data.txt",
#' out.file = "example",
#' species = species,
#' FL = FL,
#' levels = levels)
#'
#Script: panev.network.enrichment.R
#License: GPLv3 or later
#Modification date: 2019-10-17
#Written by: Valentino Palombo
#Contact: valentino.palombo@gmail.com
#Description: Descriptive statistics of data (i.e. Enrichemnt analysis, Genes per pathways, Pathways for genes)
panev.network.enrichment <- function(
in.file=NULL,
out.file="PANEV_enrich",
species=NULL,
FL = NULL,
levels = 2
)
{
#import genelist
in.file.name <- paste(in.file)
if (file.exists(in.file.name)){
genelist <<- read.table(in.file.name, header=T, stringsAsFactors = F)
cat("Input file imported! \n")
cat("\n")
#check the genelist arguments
panev.checkGenelist(genelist = genelist, type="gene")
#delete gene(s) with no entrez gene id
genelist <- genelist[!is.na(genelist$entrezgene),]
#add esembl to no symbol genes
genelist <<- panev.addExternalGeneName(genelist = genelist)
}else{
cat("Input file not found. Please check! \n")
stop("Exit",call. = F)
}
#check the path arguments
panev.checkPath(species, FL)
cat("\n")
cat("\nPrerequisite check passed!\n\nPANEV is running ... \n")
cat(" Please wait... It could take a while depending on the number of pathways and levels required! \n")
#set the levels to investigate
level <- 1:levels
#download gene/path id table
panev.downloadGenePathTable(species = species)
#add gene/path relations to genelist
genelist$KEGGgenes <- paste(paste(species),":",genelist$entrezgene, sep="")
genelist <- merge(x = genelist, y = KEGGgenes, by.x = "KEGGgenes", by.y = "V1", all=F)
#download pathways description
panev.downloadPathDescription(species = species)
#prepare FL to query on KEGG
query <- as.data.frame(gsub("map", species, FL), stringsAsFactors = F)
colnames(query) <- "path_ID"
#prepare the storage object
nextlevel <- NULL
if (length(level)>1){
#path(s) excluded for further levels
exclude <- query
for (j in 2:length(level)){
for (k in 1:length(query[,1])){
out_nodes <- suppressMessages(data.frame(do.call(rbind, (XML::getNodeSet((XML::xmlParse(KEGGREST::keggGet(query[k,1], "kgml"))), "//entry[@type='map']", fun=XML::xmlToList)))))
lks <- as.data.frame(t(as.data.frame(out_nodes$.attrs)), stringsAsFactors = F)
lks <- unique(as.data.frame(paste(lks$name), stringsAsFactors = F))
colnames(lks) <- "path_ID"
lks <- as.data.frame(subset(lks, !(lks$path_ID %in% query$path_ID)), stringsAsFactors = F)
nextlevel <- rbind(nextlevel, lks)
}
nextlevel <- unique(nextlevel)
#grab only path with species specified
nextlevel <- nextlevel[grep(species, nextlevel$path_ID, ignore.case = TRUE), ]
#grab path different from previous level
nextlevel <- nextlevel[(!(nextlevel %in% exclude$path_ID))]
#path excluded in the next levels analysis
exclude <- rbind(exclude, data.frame(path_ID = nextlevel))
query <- data.frame(path_ID = nextlevel, stringsAsFactors = F)
}
exclude <- unique(exclude)
exclude <- exclude$path_ID
cat("\nEnrichment analysis started ... ")
#perform the enrichment analysis
genes <- as.vector(unique(genelist$KEGGgenes))
KEGGgenes2 <- as.data.frame(KEGGgenes)
KEGGgenes2$V1 <- as.character(KEGGgenes2$V1)
pathquery <- gsub("map", species, exclude)
KEGGgenes2 <- KEGGgenes2[KEGGgenes2$rn %in% exclude,]
reference <- unique(paste(KEGGgenes2$V1))
pathtofind <- unique(exclude)
genesets <- list()
for (i in 1:length(pathtofind)) {
genesets[[paste(pathtofind[i])]] <- subset(KEGGgenes$V1, KEGGgenes$rn==pathtofind[i])
}
enrich <- bc3net::enrichment(genes, reference, genesets, adj = "fdr", verbose = FALSE)
enrich <- merge(x = enrich, y = KEGGpath, by.x = "TermID", by.y = "rn", all=F)
colnames(enrich) <- c("pathway_ID", "n_genes", "all_genes", "pvalue", "padj", "pathway_name")
enrich <- enrich[order(enrich$padj, enrich$pvalue),]
write.table(x = enrich, file = paste(out.file,"_net.enrichment.txt",sep=""), row.names = F)
cat("\n")
cat("Enrichment results exported! \n")
}else{
exclude <- FL
exclude <- gsub("map", species, exclude)
cat("\nEnrichment analysis started ... ")
#perform the enrichment analysis
genes <- as.vector(unique(genelist$KEGGgenes))
KEGGgenes2 <- as.data.frame(KEGGgenes)
KEGGgenes2$V1 <- as.character(KEGGgenes2$V1)
pathquery <- gsub("map", species, exclude)
KEGGgenes2 <- KEGGgenes2[KEGGgenes2$rn %in% exclude,]
reference <- unique(paste(KEGGgenes2$V1))
pathtofind <- unique(exclude)
genesets <- list()
for (i in 1:length(pathtofind)) {
genesets[[paste(pathtofind[i])]] <- subset(KEGGgenes$V1, KEGGgenes$rn==pathtofind[i])
}
enrich <- bc3net::enrichment(genes, reference, genesets, adj = "fdr", verbose = FALSE)
enrich <- merge(x = enrich, y = KEGGpath, by.x = "TermID", by.y = "rn", all=F)
colnames(enrich) <- c("pathway_ID", "n_genes", "all_genes", "pvalue", "padj", "pathway_name")
enrich <- enrich[order(enrich$padj, enrich$pvalue),]
write.table(x = enrich, file = paste(out.file,"_net.enrichment.txt",sep=""), row.names = F)
cat("\n")
cat("and results exported! \n")
}
}
vpalombo/PANEV documentation built on June 13, 2022, 1:11 p.m.
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Defines functions panev.network.enrichment
Documented in panev.network.enrichment
#' @title Enrichment analysis considering PANEV result as a background
#' @description The function perform an enrichment analysis of the genes highlighted by PANEV using the union of pathways investigated for generating the network result as a background.The result help to interpret the PANEV output and allows identifying the pathways most strongly associated with the generated gene list.
#' @usage panev.network.enrichment(in.file, out.file = "PANEV_enrich", species = NULL, FL = NULL, levels = 2)
#' @param in.file Name of input file (with extension) containing the gene list of interest. The file \bold{must} contain three columns labelled as \emph{'ensembl_gene_id'}, \emph{'entrezgene'} and \emph{'external_gene_name'}, respectively. The file \bold{must} rely in the working directory. The handy function \code{\link[PANEV]{panev.dataPreparation}} could be used to create a properly formatted input file from a single gene list.
#' @param out.file Name of the folder where the results will be stored and of the output diagram file (default = 'PANEV_enrich').
#' @param 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 \code{\link[PANEV]{panev.speciesCode}}.
#' @param FL A list of pathways of first level to investigate. The list of all available pathways can get with the \code{\link[PANEV]{panev.pathList}} function.
#' @param levels The number of levels of interactions (from \emph{1} to \emph{n}) investingated (default = 2).
#' @details This function is based on \code{\link[KEGGREST]{keggList}} and \code{\link[KEGGREST]{keggLink}} functions of \pkg{KEGGREST} package (\url{http://bioconductor.org/packages/release/bioc/html/KEGGREST.html}.
#' @details The enrichment analysis is based on \code{\link[bc3net]{enrichment}} function of \pkg{bc3net} package (\url{https://cran.r-project.org/web/packages/bc3net/index.html}.
#' @return A \emph{<out.file>_net.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 Valentino Palombo (\email{valentino.palombo@gmail.com})
#' @references Tenenbaum D (2017). KEGGREST: Client-side REST access to KEGG. R package version 1.16.1.
#' @references 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
#'
#' #Specify the first level pathways to investigate
#' FL = c("path:map00061", "path:map00062", "path:map00071", "path:map00072")
#' #Specify the number of levels of pathways to investigate
#' levels = 3
#'
#' #Run the PANEV enrichment function
#' panev.network.enrichment(in.file = "data.txt",
#' out.file = "example",
#' species = species,
#' FL = FL,
#' levels = levels)
#'
#Script: panev.network.enrichment.R
#License: GPLv3 or later
#Modification date: 2019-10-17
#Written by: Valentino Palombo
#Contact: valentino.palombo@gmail.com
#Description: Descriptive statistics of data (i.e. Enrichemnt analysis, Genes per pathways, Pathways for genes)
panev.network.enrichment <- function(
in.file=NULL,
out.file="PANEV_enrich",
species=NULL,
FL = NULL,
levels = 2
)
{
#import genelist
in.file.name <- paste(in.file)
if (file.exists(in.file.name)){
genelist <<- read.table(in.file.name, header=T, stringsAsFactors = F)
cat("Input file imported! \n")
cat("\n")
#check the genelist arguments
panev.checkGenelist(genelist = genelist, type="gene")
#delete gene(s) with no entrez gene id
genelist <- genelist[!is.na(genelist$entrezgene),]
#add esembl to no symbol genes
genelist <<- panev.addExternalGeneName(genelist = genelist)
}else{
cat("Input file not found. Please check! \n")
stop("Exit",call. = F)
}
#check the path arguments
panev.checkPath(species, FL)
cat("\n")
cat("\nPrerequisite check passed!\n\nPANEV is running ... \n")
cat(" Please wait... It could take a while depending on the number of pathways and levels required! \n")
#set the levels to investigate
level <- 1:levels
#download gene/path id table
panev.downloadGenePathTable(species = species)
#add gene/path relations to genelist
genelist$KEGGgenes <- paste(paste(species),":",genelist$entrezgene, sep="")
genelist <- merge(x = genelist, y = KEGGgenes, by.x = "KEGGgenes", by.y = "V1", all=F)
#download pathways description
panev.downloadPathDescription(species = species)
#prepare FL to query on KEGG
query <- as.data.frame(gsub("map", species, FL), stringsAsFactors = F)
colnames(query) <- "path_ID"
#prepare the storage object
nextlevel <- NULL
if (length(level)>1){
#path(s) excluded for further levels
exclude <- query
for (j in 2:length(level)){
for (k in 1:length(query[,1])){
out_nodes <- suppressMessages(data.frame(do.call(rbind, (XML::getNodeSet((XML::xmlParse(KEGGREST::keggGet(query[k,1], "kgml"))), "//entry[@type='map']", fun=XML::xmlToList)))))
lks <- as.data.frame(t(as.data.frame(out_nodes$.attrs)), stringsAsFactors = F)
lks <- unique(as.data.frame(paste(lks$name), stringsAsFactors = F))
colnames(lks) <- "path_ID"
lks <- as.data.frame(subset(lks, !(lks$path_ID %in% query$path_ID)), stringsAsFactors = F)
nextlevel <- rbind(nextlevel, lks)
}
nextlevel <- unique(nextlevel)
#grab only path with species specified
nextlevel <- nextlevel[grep(species, nextlevel$path_ID, ignore.case = TRUE), ]
#grab path different from previous level
nextlevel <- nextlevel[(!(nextlevel %in% exclude$path_ID))]
#path excluded in the next levels analysis
exclude <- rbind(exclude, data.frame(path_ID = nextlevel))
query <- data.frame(path_ID = nextlevel, stringsAsFactors = F)
}
exclude <- unique(exclude)
exclude <- exclude$path_ID
cat("\nEnrichment analysis started ... ")
#perform the enrichment analysis
genes <- as.vector(unique(genelist$KEGGgenes))
KEGGgenes2 <- as.data.frame(KEGGgenes)
KEGGgenes2$V1 <- as.character(KEGGgenes2$V1)
pathquery <- gsub("map", species, exclude)
KEGGgenes2 <- KEGGgenes2[KEGGgenes2$rn %in% exclude,]
reference <- unique(paste(KEGGgenes2$V1))
pathtofind <- unique(exclude)
genesets <- list()
for (i in 1:length(pathtofind)) {
genesets[[paste(pathtofind[i])]] <- subset(KEGGgenes$V1, KEGGgenes$rn==pathtofind[i])
}
enrich <- bc3net::enrichment(genes, reference, genesets, adj = "fdr", verbose = FALSE)
enrich <- merge(x = enrich, y = KEGGpath, by.x = "TermID", by.y = "rn", all=F)
colnames(enrich) <- c("pathway_ID", "n_genes", "all_genes", "pvalue", "padj", "pathway_name")
enrich <- enrich[order(enrich$padj, enrich$pvalue),]
write.table(x = enrich, file = paste(out.file,"_net.enrichment.txt",sep=""), row.names = F)
cat("\n")
cat("Enrichment results exported! \n")
}else{
exclude <- FL
exclude <- gsub("map", species, exclude)
cat("\nEnrichment analysis started ... ")
#perform the enrichment analysis
genes <- as.vector(unique(genelist$KEGGgenes))
KEGGgenes2 <- as.data.frame(KEGGgenes)
KEGGgenes2$V1 <- as.character(KEGGgenes2$V1)
pathquery <- gsub("map", species, exclude)
KEGGgenes2 <- KEGGgenes2[KEGGgenes2$rn %in% exclude,]
reference <- unique(paste(KEGGgenes2$V1))
pathtofind <- unique(exclude)
genesets <- list()
for (i in 1:length(pathtofind)) {
genesets[[paste(pathtofind[i])]] <- subset(KEGGgenes$V1, KEGGgenes$rn==pathtofind[i])
}
enrich <- bc3net::enrichment(genes, reference, genesets, adj = "fdr", verbose = FALSE)
enrich <- merge(x = enrich, y = KEGGpath, by.x = "TermID", by.y = "rn", all=F)
colnames(enrich) <- c("pathway_ID", "n_genes", "all_genes", "pvalue", "padj", "pathway_name")
enrich <- enrich[order(enrich$padj, enrich$pvalue),]
write.table(x = enrich, file = paste(out.file,"_net.enrichment.txt",sep=""), row.names = F)
cat("\n")
cat("and results exported! \n")
}
}
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