Nothing
## ----style, echo=FALSE, results='asis', message=FALSE-------------------------
knitr::opts_chunk$set(tidy = FALSE,
warning = FALSE,
message = FALSE)
CRANpkg <- function (pkg) {
cran <- "https://CRAN.R-project.org/package"
fmt <- "[%s](%s=%s)"
sprintf(fmt, pkg, cran, pkg)
}
Biocpkg <- function (pkg) {
sprintf("[%s](http://bioconductor.org/packages/%s)", pkg, pkg)
}
Biocannopkg <- Biocpkg
## ----echo=FALSE, results='hide', message=FALSE--------------------------------
library(GenomicFeatures)
library(GenomicRanges)
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
library(org.Hs.eg.db)
library(ggplot2)
library(clusterProfiler)
library(ReactomePA)
library(ChIPseeker)
## -----------------------------------------------------------------------------
## loading packages
library(ChIPseeker)
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
library(clusterProfiler)
## -----------------------------------------------------------------------------
files <- getSampleFiles()
print(files)
peak <- readPeakFile(files[[4]])
peak
## ----fig.height=8, fig.width=10-----------------------------------------------
covplot(peak, weightCol="V5")
## ----fig.height=4, fig.width=10-----------------------------------------------
covplot(peak, weightCol="V5", chrs=c("chr17", "chr18"), xlim=c(4.5e7, 5e7))
## -----------------------------------------------------------------------------
## promoter <- getPromoters(TxDb=txdb, upstream=3000, downstream=3000)
## tagMatrix <- getTagMatrix(peak, windows=promoter)
##
## to speed up the compilation of this vignettes, we use a precalculated tagMatrix
data("tagMatrixList")
tagMatrix <- tagMatrixList[[4]]
## ----fig.cap="Heatmap of ChIP peaks binding to TSS regions", fig.align="center", fig.height=12, fig.width=4----
tagHeatmap(tagMatrix, xlim=c(-3000, 3000), color="red")
## ----eval=FALSE---------------------------------------------------------------
# peakHeatmap(files[[4]], TxDb=txdb, upstream=3000, downstream=3000, color="red")
## ----eval=TRUE, fig.cap="Average Profile of ChIP peaks binding to TSS region", fig.align="center", fig.height=4, fig.width=7----
plotAvgProf(tagMatrix, xlim=c(-3000, 3000),
xlab="Genomic Region (5'->3')", ylab = "Read Count Frequency")
## ----eval=FALSE---------------------------------------------------------------
# plotAvgProf2(files[[4]], TxDb=txdb, upstream=3000, downstream=3000,
# xlab="Genomic Region (5'->3')", ylab = "Read Count Frequency")
## ----fig.cap="Average Profile of ChIP peaks binding to TSS region", fig.align="center", fig.height=4, fig.width=7, eval=F----
# plotAvgProf(tagMatrix, xlim=c(-3000, 3000), conf = 0.95, resample = 1000)
## -----------------------------------------------------------------------------
peakAnno <- annotatePeak(files[[4]], tssRegion=c(-3000, 3000),
TxDb=txdb, annoDb="org.Hs.eg.db")
## ----fig.cap="Genomic Annotation by pieplot", fig.align="center", fig.height=6, fig.width=8----
plotAnnoPie(peakAnno)
## ----fig.cap="Genomic Annotation by barplot", fig.align="center", fig.height=4, fig.width=10----
plotAnnoBar(peakAnno)
## ----fig.cap="Genomic Annotation by vennpie", fig.align="center", fig.height=8, fig.width=11----
vennpie(peakAnno)
## ----eval=F, fig.cap="Genomic Annotation by upsetplot", fig.align="center", fig.height=8, fig.width=12----
# upsetplot(peakAnno)
## ----eval=F, fig.cap="Genomic Annotation by upsetplot", fig.align="center", fig.height=8, fig.width=12----
# upsetplot(peakAnno, vennpie=TRUE)
## ----fig.cap="Distribution of Binding Sites", fig.align="center", fig.height=2, fig.width=6----
plotDistToTSS(peakAnno,
title="Distribution of transcription factor-binding loci\nrelative to TSS")
## ----fig.width=8, fig.height=5------------------------------------------------
library(ReactomePA)
pathway1 <- enrichPathway(as.data.frame(peakAnno)$geneId)
head(pathway1, 2)
gene <- seq2gene(peak, tssRegion = c(-1000, 1000), flankDistance = 3000, TxDb=txdb)
pathway2 <- enrichPathway(gene)
head(pathway2, 2)
dotplot(pathway2)
## ----eval=TRUE, fig.cap="Average Profiles of ChIP peaks among different experiments", fig.align="center", fig.height=4, fig.width=6----
## promoter <- getPromoters(TxDb=txdb, upstream=3000, downstream=3000)
## tagMatrixList <- lapply(files, getTagMatrix, windows=promoter)
##
## to speed up the compilation of this vigenette, we load a precaculated tagMatrixList
data("tagMatrixList")
plotAvgProf(tagMatrixList, xlim=c(-3000, 3000))
## ----eval=FALSE, fig.cap="Average Profiles of ChIP peaks among different experiments", fig.align="center", fig.height=7, fig.width=6----
# plotAvgProf(tagMatrixList, xlim=c(-3000, 3000), conf=0.95,resample=500, facet="row")
## ----eval=TRUE, fig.cap="Heatmap of ChIP peaks among different experiments", fig.align="center", fig.height=8, fig.width=7----
tagHeatmap(tagMatrixList, xlim=c(-3000, 3000), color=NULL)
## -----------------------------------------------------------------------------
peakAnnoList <- lapply(files, annotatePeak, TxDb=txdb,
tssRegion=c(-3000, 3000), verbose=FALSE)
## ----fig.cap="Genomic Annotation among different ChIPseq data", fig.align="center", fig.height=4, fig.width=6----
plotAnnoBar(peakAnnoList)
## ----fig.cap="Distribution of Binding Sites among different ChIPseq data", fig.align="center", fig.height=5, fig.width=8----
plotDistToTSS(peakAnnoList)
## ----fig.width=8.5, fig.height=8.5--------------------------------------------
genes = lapply(peakAnnoList, function(i) as.data.frame(i)$geneId)
names(genes) = sub("_", "\n", names(genes))
compKEGG <- compareCluster(geneCluster = genes,
fun = "enrichKEGG",
pvalueCutoff = 0.05,
pAdjustMethod = "BH")
dotplot(compKEGG, showCategory = 15, title = "KEGG Pathway Enrichment Analysis")
## ----fig.cap="Overlap of annotated genes", fig.align="center", fig.height=7, fig.width=7----
genes= lapply(peakAnnoList, function(i) as.data.frame(i)$geneId)
vennplot(genes)
## -----------------------------------------------------------------------------
p <- GRanges(seqnames=c("chr1", "chr3"),
ranges=IRanges(start=c(1, 100), end=c(50, 130)))
shuffle(p, TxDb=txdb)
## -----------------------------------------------------------------------------
enrichPeakOverlap(queryPeak = files[[5]],
targetPeak = unlist(files[1:4]),
TxDb = txdb,
pAdjustMethod = "BH",
nShuffle = 50,
chainFile = NULL,
verbose = FALSE)
## -----------------------------------------------------------------------------
getGEOspecies()
## -----------------------------------------------------------------------------
getGEOgenomeVersion()
## -----------------------------------------------------------------------------
hg19 <- getGEOInfo(genome="hg19", simplify=TRUE)
head(hg19)
## ----eval=FALSE---------------------------------------------------------------
# downloadGEObedFiles(genome="hg19", destDir="hg19")
## ----eval=FALSE---------------------------------------------------------------
# gsm <- hg19$gsm[sample(nrow(hg19), 10)]
# downloadGSMbedFiles(gsm, destDir="hg19")
## ----echo=FALSE---------------------------------------------------------------
sessionInfo()
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