Nothing
## ----query_region-------------------------------------------------------------
require(GenomicRanges)
bed.file <- system.file("extdata", "query/Psoriasis.BED", package = "loci2path")
query.bed <- read.table(bed.file, header=FALSE)
colnames(query.bed) <- c("chr","start","end")
query.gr <- makeGRangesFromDataFrame(query.bed)
## ----eset---------------------------------------------------------------------
library(loci2path)
library(GenomicRanges)
brain.file <- system.file("extdata", "eqtl/brain.gtex.txt",
package="loci2path")
tab <- read.table(brain.file, stringsAsFactors=FALSE, header=TRUE)
snp.gr <- GRanges(seqnames=Rle(tab$snp.chr),
ranges=IRanges(start=tab$snp.pos,
width=1))
brain.eset <- eqtlSet(tissue="brain",
eqtlId=tab$snp.id,
eqtlRange=snp.gr,
gene=as.character(tab$gene.entrez.id))
brain.eset
skin.file <- system.file("extdata", "eqtl/skin.gtex.txt", package="loci2path")
tab=read.table(skin.file, stringsAsFactors=FALSE, header=TRUE)
snp.gr <- GRanges(seqnames=Rle(tab$snp.chr),
ranges=IRanges(start=tab$snp.pos,
width=1))
skin.eset <- eqtlSet(tissue="skin",
eqtlId=tab$snp.id,
eqtlRange=snp.gr,
gene=as.character(tab$gene.entrez.id))
skin.eset
blood.file <- system.file("extdata", "eqtl/blood.gtex.txt",
package="loci2path")
tab <- read.table(blood.file, stringsAsFactors=FALSE, header=TRUE)
snp.gr <- GRanges(seqnames=Rle(tab$snp.chr),
ranges=IRanges(start=tab$snp.pos,
width=1))
blood.eset <- eqtlSet(tissue="blood",
eqtlId=tab$snp.id,
eqtlRange=snp.gr,
gene=as.character(tab$gene.entrez.id))
blood.eset
## ----esetlist-----------------------------------------------------------------
eset.list <- list(Brain=brain.eset, Skin=skin.eset, Blood=blood.eset)
eset.list
## -----------------------------------------------------------------------------
biocarta.link.file <- system.file("extdata", "geneSet/biocarta.txt",
package="loci2path")
biocarta.set.file <- system.file("extdata", "geneSet/biocarta.set.txt",
package="loci2path")
biocarta.link <- read.delim(biocarta.link.file, header=FALSE,
stringsAsFactors=FALSE)
set.geneid <- read.table(biocarta.set.file, stringsAsFactors=FALSE)
set.geneid <- strsplit(set.geneid[,1], split=",")
names(set.geneid) <- biocarta.link[,1]
head(biocarta.link)
head(set.geneid)
## -----------------------------------------------------------------------------
#build geneSet
biocarta <- geneSet(
numGene=31847,
description=biocarta.link[,2],
geneSetList=set.geneid)
biocarta
## -----------------------------------------------------------------------------
#query from one eQTL set.
res.one <- query(
query.gr=query.gr,
loci=skin.eset,
path=biocarta)
#enrichment result table
res.one$result.table
#all the genes associated with eQTLs covered by the query region
res.one$cover.gene
## -----------------------------------------------------------------------------
#query from one eQTL set.
res.esetlist <- query(
query.gr=query.gr,
loci=eset.list,
path=biocarta)
#enrichment result table, tissue column added
resultTable(res.esetlist)
#all the genes associated with eQTLs covered by the query region;
#names of the list are tissue names from eqtl set list
coveredGene(res.esetlist)
## -----------------------------------------------------------------------------
#query from one eQTL set.
res.paral <- query(
query.gr=query.gr,
loci=eset.list,
path=biocarta,
parallel=TRUE)
#should return the same result as res.esetlist
## -----------------------------------------------------------------------------
result <- resultTable(res.esetlist)
## -----------------------------------------------------------------------------
#all the genes associated with eQTLs covered by the query region
res.one$cover.gene
#all the genes associated with eQTLs covered by the query region;
#names of the list are tissue names from eqtl set list
coveredGene(res.esetlist)
## -----------------------------------------------------------------------------
tissue.degree <- getTissueDegree(res.esetlist, eset.list)
#check gene-tissue mapping for each gene
head(tissue.degree$gene.tissue.map)
#check degree for each gene
head(tissue.degree$gene.tissue.degree)
#average tissue degree for the input result table
tissue.degree$mean.tissue.degree
#add avg. tissue degree to existing result table
res.tissue <- data.frame(resultTable(res.esetlist),
t.degree=tissue.degree$mean.tissue.degree)
## -----------------------------------------------------------------------------
#query tissue specificity
gr.tissue <- query(query.gr, loci=eset.list)
gr.tissue
## -----------------------------------------------------------------------------
#extract tissue-pathway matrix
mat <- getMat(res.esetlist, test.method="gene")
#plot heatmap
heatmap.para <- getHeatmap(res.esetlist)
## -----------------------------------------------------------------------------
#plot word cloud
wc <- getWordcloud(res.esetlist)
## -----------------------------------------------------------------------------
#plot p-value distribution of result
pval <- getPval(res.esetlist, test.method="gene")
## -----------------------------------------------------------------------------
#obtain geneset description from object
description <- getPathDescription(res.esetlist, biocarta)
head(description)
## ----sessionInfo, echo=FALSE--------------------------------------------------
sessionInfo()
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