In aiminy/PathwaySplice: An R Package for Adjusting Bias in Gene Set Enrichment Analysis

The tutorial to use PathwaySplice

• Run DEXSeq or JunctionSeq to get differential exon and/or splicing junction analysis resutls

dir.name="/media/H_driver/Aimin_project/"

file.sample="decoder.bySample.Mut_WT_2.rtf"
file.gff="Homo_sapiens.GRCh38.84.processed.sorted.4.JunctionSeq.flat.gff"

file.count="/QC.spliceJunctionAndExonCounts.forJunctionSeq.txt"

Re.example<-GetResultsFromJunctionSeq(dir.name,file.sample,file.count,file.gff)

• Convert the results of differential usage analysis into gene based resutls

re.example.gene.based<-makeGeneWiseTable(Re.example,gene.list=unique(as.character(fData(Re.example)$geneID)))

• Apply logistic regression model to identify bias factor

library(PathwaySplice)
data(mds)
hist(as.numeric(mds$numExons),xlab="Number of exons",main="Distribution of number of exons")

re<-LRtestBias(mds,boxplot_width=0.3)

• Perform pathwaysplice in one step

library(PathwaySplice)
data(mds)
data(hg19)
Example.Go.adjusted.by.exon.Wallenius<-Run_pathwaysplice(mds,ad="exon_SJ",sub_feature="E",0.05,genomeID="hg19",geneID="ensGene",gene_model=hg19,method="Wallenius")
Example.Go.adjusted.by.exon.sampling<-Run_pathwaysplice(mds,ad="exon_SJ",sub_feature="E",0.05,genomeID="hg19",geneID="ensGene",gene_model=hg19,method="Sampling")
Example.Go.unadjusted<-Run_pathwaysplice(mds,ad="exon_SJ",sub_feature="E",0.05,genomeID="hg19",geneID="ensGene",gene_model=hg19,method="Hypergeometric")

• If you are interested in other gene sets such as Canonical Pathways(CP),Transcription Factor Targets(TFT) and hallmark gene sets from http://software.broadinstitute.org/gsea/msigdb/collections.jsp, download these .gmt files, then perform the following steps:

gene.2.cat.hallmark.hg<-Gmt2GeneCat("/media/H_driver/Annotation/hg38/h.all.v5.1.symbols-1.gmt","local","/media/H_driver/Annotation/hg38/genes_table_02092016.csv")

#read from url
# it works, but you need to get the correct url for h.all.v5.1.symbols-1.gmt file
#gene.2.cat.hallmark.hg.from.url<-Gmt2GeneCat("ftp://ftp.broad.mit.edu/distribution/gsea/gene_sets/msigdb.v4.0c.symbols.gmt","url","/media/H_driver/Annotation/hg38/genes_table_02092016.csv")

• Build up network based on the overlap between gene sets and visualize this network

data(mds)
Example.Go.adjusted.by.exon<-Run_pathwaysplice(mds,ad="exon_SJ",sub_feature="E",0.05,genomeID="hg19",geneID="ensGene",gene_model=hg19.gene.model,method="Wallenius")
re.w.adjusted<-enrichmentMap(Example.Go.adjusted.by.exon,n=5,SimilarityThreshold=0)

aiminy/PathwaySplice documentation built on May 10, 2019, 7:38 a.m.