############################################## # Example 1 - find the nearest TSS for the peaks ############################################## library(ChIPpeakAnno) data(myPeakList) data(TSS.human.GRCh37) annotatedPeak = annotatePeakInBatch (myPeakList[1:6,], AnnotationData = TSS.human.GRCh37) #The annotated peaks can be saved as an Excel file for biologists to view easily. write.table(as.data.frame(annotatedPeak), file="annotatedPeakList.xls", sep="\t", row.names=FALSE) ############################################## # Example 2 - Plot the distribution of the peaks relative to the TSS # Gives a birds-eye view of the peak distribution relative to the genomic features of interest. ############################################## data(annotatedPeak) y = annotatedPeak\$distancetoFeature[!is.na(annotatedPeak\$distancetoFeature) & annotatedPeak\$fromOverlappingOrNearest == "NearestStart"] hist(y, xlab="Distance To Nearest TSS", main="", breaks=1000, xlim=c(min(y)-100, max(y)+100)) temp = as.data.frame(annotatedPeak) plot(density(y)) y = annotatedPeak\$distancetoFeature[!is.na(annotatedPeak\$distancetoFeature) & annotatedPeak\$fromOverlappingOrNearest == "NearestStart" & abs(annotatedPeak\$distancetoFeature) <10000] pie(table(temp[as.character(temp\$fromOverlappingOrNearest) == "Overlapping" | (as.character(temp\$fromOverlappingOrNearest) == "NearestStart" & !temp\$peak %in% temp[as.character(temp\$fromOverlappingOrNearest) == "Overlapping", ]\$peak) ,]\$insideFeature)) ############################################## # Example 3 - Obtain annotation on-line using getAnnotation ############################################## mart = useMart(biomart="ensembl", dataset="hsapiens_gene_ensembl") #Annotation = getAnnotation(mart, featureType="TSS") Annotation = getAnnotation(mart, featureType="miRNA") as.data.frame(Annotation)[1:10,] ############################################## # Example 4 - Label the peaks from your experiment with a list of peaks in the literature # including both nearest and overlapping sites ############################################## myexp = RangedData(IRanges(start=c(1543200,1557200,1563000,1569800, 167889600,100,1000), end=c(1555199,1560599,1565199,1573799, 167893599,200,1200), names=c("p1","p2","p3","p4","p5","p6", "p7")), strand=as.integer(1),space=c(6,6,6,6,5,4,4)) literature = RangedData(IRanges(start=c(1549800,1554400,1565000,1569400,167888600,120,800), end=c(1550599,1560799,1565399,1571199,167888999,140,1400), names=c("f1","f2","f3","f4","f5","f6","f7")), strand=c(1,1,1,1,1,-1,-1), space=c(6,6,6,6,5,4,4)) annotatedPeak1= annotatePeakInBatch(myexp, AnnotationData = literature, output="both", maxgap=1000, multiple=TRUE) pie(table(as.data.frame(annotatedPeak1)\$insideFeature)) as.data.frame(annotatedPeak1) ##### different parameter setting annotatedPeak1= annotatePeakInBatch(myexp, AnnotationData = literature, output="overlapping", maxgap=1000, multiple=TRUE) as.data.frame(annotatedPeak1) annotatedPeak1= annotatePeakInBatch(myexp, AnnotationData = literature, output="nearestStart", PeakLocForDistance ="middle", FeatureLocForDistance="middle") as.data.frame(annotatedPeak1) ############################################## # Example 5 - BED2RangedData and GFF2RangedData ############################################## test.bed = data.frame(cbind(chrom = c("4", "6"), chromStart=c("100", "1000"),chromEnd=c("200", "1100"), name=c("peak1", "peak2"))) test.rangedData = BED2RangedData(test.bed) as.data.frame(annotatePeakInBatch(test.rangedData, AnnotationData = literature)) test.GFF = data.frame(cbind(seqname = c("chr4", "chr4"), source=rep("Macs", 2), feature=rep("peak", 2), start=c("100", "1000"), end=c("200", "1100"), score=c(60, 26), strand=c(1, 1), frame=c(".", 2), group=c("peak1", "peak2"))) test.rangedData = GFF2RangedData(test.GFF) as.data.frame(annotatePeakInBatch(test.rangedData, AnnotationData = literature)) ############################################## # Example 6 - Determine the significance of the overlapping and # visualize the overlap as a Venn diagram among different datasets ############################################## data(Peaks.Ste12.Replicate1) data(Peaks.Ste12.Replicate2) data(Peaks.Ste12.Replicate3) makeVennDiagram(RangedDataList(Peaks.Ste12.Replicate1, Peaks.Ste12.Replicate2, Peaks.Ste12.Replicate3), NameOfPeaks = c("Replicate1","Replicate2","Replicate3"), maxgap = 0, totalTest = 1580) #Combine the Overlapping Peaks Across Replicates MergedPeaks = findOverlappingPeaks(findOverlappingPeaks(Peaks.Ste12.Replicate1, Peaks.Ste12.Replicate2, maxgap = 0, multiple = F, NameOfPeaks1 = "R1", NameOfPeaks2 = "R2")\$MergedPeaks, Peaks.Ste12.Replicate3, maxgap = 0, multiple = F, NameOfPeaks1 = "R1R2", NameOfPeaks2 = "R3")\$MergedPeak as.data.frame(MergedPeaks) ############################################## # Example 7 - Obtain the sequences around the binding sites for PCR amplification or motif discovery ############################################## peaks = RangedData(IRanges(start = c(100, 500), end = c(300, 600), names = c("peak1", "peak2")), space = c("NC_008253", "NC_010468")) library(BSgenome.Ecoli.NCBI.20080805) peaksWithSequences = getAllPeakSequence(peaks, upstream = 100, downstream = 100, genome = Ecoli) write2FASTA(peaksWithSequences, file="test.fa", width=50) #available.genomes() ############################################## # Example 8 - Obtain enriched GO terms near the peaks ############################################## data(annotatedPeak) library(org.Hs.eg.db) enrichedGO <- getEnrichedGO (annotatedPeak[1:6,], orgAnn="org.Hs.eg.db", maxP=0.1, multiAdj =TRUE, minGOterm=1, multiAdjMethod="BH") ############################################## # Example 9 - Find the peaks with bi-directional promoters with summary statistics (>= version1.9.6) ############################################## temp = peaksNearBDP(myPeakList[1:10,], AnnotationData=TSS.human.GRCh37, MaxDistance=5000, PeakLocForDistance="middle", FeatureLocForDistance = "TSS") c(temp\$percentPeaksWithBDP, temp\$n.peaksWithBDP, temp\$n.peaks) temp\$peaksWithBDP ############################################## # Example 10 - Summarize the occurrence of motifs in peaks (>= version1.9.6) ############################################## filePath = system.file("extdata", "examplePattern.fa", package="ChIPpeakAnno") summarizePatternInPeaks(patternFilePath=filePath,skip=0L, format="fasta", BSgenomeName=Ecoli , peaks=peaks, outfile="testExample10.xls", append=FALSE) file.remove("testExample10.xls")