{"id":618,"date":"2021-01-05T18:50:59","date_gmt":"2021-01-05T10:50:59","guid":{"rendered":"http:\/\/www.wuchangsong.com\/?p=618"},"modified":"2021-04-09T10:54:56","modified_gmt":"2021-04-09T02:54:56","slug":"atac-seq%e5%88%86%e6%9e%90%e6%b5%81%e7%a8%8b%ef%bc%88%e4%ba%8c%ef%bc%89","status":"publish","type":"post","link":"http:\/\/www.wuchangsong.com\/?p=618","title":{"rendered":"ATAC-seq\u5206\u6790\u6d41\u7a0b\uff08\u4e8c\uff09"},"content":{"rendered":"

\u516d\u3001Deeptools\u53ef\u89c6\u5316<\/p>\n

#deeptools\u5b89\u88c5conda install deeptools\ngtf2bed < ~\/gc_genome\/17.Geta\/1.geta\/out.gtf > genome.bed\nfor i in `cat ..\/samples.txt`; do echo \"bamCoverage -p 5 --normalizeUsing RPKM -b $i.last.bam -o $i.last.bw\"; done > bam2bw.list\nParaFly -c bam2bw.list -CPU 9\ncomputeMatrix reference-point  --referencePoint TSS  -p 15 -b 10000 -a 10000 -R ..\/genome.bed -S ..\/*bw --skipZeros  -o matrix1_test_TSS.gz --outFileSortedRegions regions1_test_genes.bed\nplotHeatmap -m matrix1_test_TSS.gz  -out test_Heatmap.pdf --plotFileFormat pdf  --dpi 720\nplotProfile -m matrix1_test_TSS.gz  -out test_Profile.pdf --plotFileFormat pdf --perGroup --dpi 720\ncomputeMatrix scale-regions -p 150 -b 10000 -a 10000 -R ..\/genome.bed -S ..\/*bw --skipZeros  -o matrix1_test_body.gz --outFileSortedRegions regions1_test_body.bed\nplotHeatmap -m matrix1_test_TSS.gz  -out test_Heatmap.pdf --plotFileFormat pdf  --dpi 720\nplotProfile -m matrix1_test_TSS.gz  -out test_Profile.pdf --plotFileFormat pdf --perGroup --dpi 720\n<\/pre>\n
\u4e03\u3001\u91cd\u590d\u6837\u54c1\u5904\u7406\uff08\u81f3\u5c11\u4e24\u4e2a\u751f\u7269\u5b66\u91cd\u590d\uff09
\nIDR\u662f\u901a\u8fc7\u6bd4\u8f83\u4e00\u5bf9\u7ecf\u8fc7\u6392\u5e8f\u7684regions\/peaks \u7684\u5217\u8868\uff0c\u7136\u540e\u8ba1\u7b97\u53cd\u6620\u5176\u91cd\u590d\u6027\u7684\u503c\uff0c\u540c\u65f6\u5f97\u5230\u4e86merge\u540e\u7684\u4e00\u81f4\u6027\u7684peaks\u3002<\/p>\n
for i in `cat ..\/..\/samples.txt`; do echo \"sort -k8,8nr ..\/$i.peaks_peaks.narrowPeak > $i.peaks.narrowPeak\"; done > peaks_sort.list\nParaFly -c peaks_sort.list -CPU 9\n\n<\/pre>\n
\u516b\u3001peaks\u6ce8\u91ca\uff08\u975e\u6a21\u5f0f\u7269\u79cd\uff09
\n\u4f7f\u7528GenomicFeatures\u5305\u7684\u51fd\u6570\u5236\u4f5cTxDb\u5bf9\u8c61\uff1a<\/p>\n
#makeTxDbFromUCSC\uff1a \u901a\u8fc7UCSC\u5728\u7ebf\u5236\u4f5cTxDb\n#makeTxDbFromBiomart: \u901a\u8fc7ensembl\u5728\u7ebf\u5236\u4f5cTxDb\n#makeTxDbFromGRanges\uff1a\u901a\u8fc7GRanges\u5bf9\u8c61\u5236\u4f5cTxDb\n#makeTxDbFromGFF\uff1a\u901a\u8fc7\u89e3\u6790GFF\u6587\u4ef6\u5236\u4f5cTxDb\ngc_TxDB <- makeTxDbFromGFF(\"genome.gff3\")\nlibrary(clusterProfiler)\nlibrary(\"ChIPseeker\")\nlibrary(ChIPpeakAnno)\nlibrary(GenomicFeatures)\nlibrary(\"ggupset\")\nlibrary(\"ggimage\")\ngc_TxDB <- makeTxDbFromGFF(\"out.gff3\")\npromoter <- getPromoters(TxDb=gc_TxDB, upstream=3000, downstream=3000)\nfiles = list(A_summits = \"A.peaks_summits.bed\", B_summits = \"B.peaks_summits.bed\", C_summits = \"C.peaks_summits.bed\", D_summits = \"D.peaks_summits.bed\")\npeakAnno <- annotatePeak(files[[1]], tssRegion=c(-3000, 3000), TxDb=gc_TxDB)\nplotAnnoPie(peakAnno)\n#tiff(\"peakAnno.tiff\")\n#plotAnnoPie(peakAnno)\n#dev.off() \u6b64\u65b9\u6cd5\u4fdd\u5b58\u7684\u56fe\u7247\u6807\u6ce8\u6709\u989c\u8272\u6a21\u5757\nplotAnnoBar(peakAnno)\nvennpie(peakAnno)\npeakAnnoList <- lapply(files, annotatePeak, TxDb=gc_TxDB,tssRegion=c(-3000, 3000))\nplotAnnoBar(peakAnnoList)\n#tagHeatmap\u6765\u753b\u70ed\u56fe\npeak <- readPeakFile(files[[3]])\ntagMatrix <- getTagMatrix(peak, windows=promoter)\ntagHeatmap(tagMatrix, xlim=c(-3000, 3000), color=\"red\")\npeakHeatmap(files, TxDb=gc_TxDB, \n    upstream=3000, downstream=3000, \n    color=rainbow(length(files)))\n#\u4ee5\u8c31\u56fe\u7684\u5f62\u5f0f\u6765\u5c55\u793a\u7ed3\u5408\u7684\u5f3a\u5ea6\nplotAvgProf2(files[[3]], TxDb=gc_TxDB, \n\t\t\t upstream=3000, downstream=3000,\n             xlab=\"Genomic Region (5'->3')\", \n             ylab = \"Read Count Frequency\")\ntagMatrixList <- lapply(files, getTagMatrix, \n                        windows=promoter)\nplotAvgProf(tagMatrixList, xlim=c(-3000, 3000))\n#\u6ce8\u91ca\u57fa\u56e0\npeakAnnoList <- lapply(files, annotatePeak, TxDb=gc_TxDB,tssRegion=c(-3000, 3000),addFlankGeneInfo=TRUE, flankDistance=5000)\ngenes = lapply(peakAnnoList, function(i) as.data.frame(i)$geneId)\nvennplot(genes)\nsave(peakAnnoList,file=\"peakAnnolist.rda\")\nwrite.table(as.data.frame(peakAnnoList$mulvscon),file=\"Nanog.PeakAnno\",sep='\\t',quote = F)\n<\/pre>\n
\u4e5d\u3001\u5dee\u5f02\u5206\u6790
\nDiffBind\u5b89\u88c5<\/p>\n
conda install libv8\nconda install -c conda-forge librsvg\n##R version 4.0.3 (2020-10-10)\nBiocManager::install(\"systemPipeR\")\nBiocManager::install(\"DiffBind\")\nlibrary(DiffBind)\nsetwd(\"D:\/Experiment_data\/wcs\/ATAC\/\")\ntamoxifen <- dba(sampleSheet=\"sheet_ATAC.CSV\")\ntamoxifen <- dba.count(tamoxifen, bUseSummarizeOverlaps=TRUE)\nplot(tamoxifen)\ntamoxifen <- dba.contrast(tamoxifen, categories = DBA_FACTOR, minMembers = 3)\ntamoxifen <- dba.analyze(tamoxifen, method = DBA_DESEQ2)\n#heatmap\nhmap <- colorRampPalette(c(\"green\", \"black\", \"red\"))(n = 13)\ndba.plotHeatmap(tamoxifen, correlations=FALSE, scale=\"row\", colScheme = hmap)\n#MA plots\ndba.plotMA(tamoxifen, contrast = 2)\n#\u706b\u5c71\u56fe\ndba.plotVolcano(tamoxifen)\ntamoxifen.DB <- dba.report(tamoxifen,  method=DBA_DESEQ2, contrast = 1, th=1)\n#write.csv(tamoxifen.DB,\"diffbind.csv\")\nout <- as.data.frame(tamoxifen.DB)\nwrite.table(out, file=\"tamoxifen_DB.csv\", sep=\",\", quote=F, col.names = NA)\n#\u4fdd\u5b58\u4e0d\u540c\u6837\u672c\u7684\u8868\u8fbe\u77e9\u9635\nout <- as.data.frame(tamoxifen[[\"binding\"]])\nwrite.table(out, file=\"deseq2_count.xls\", sep=\"\\t\", quote=F, row.names=F, col.names=F)\n#\u4ee5bed\u683c\u5f0f\u4fdd\u5b58\u663e\u8457\u6027\u7684\u5dee\u5f02\u7ed3\u679c\nout <- as.data.frame(tamoxifen.DB)\ndeseq.bed <- out[ which(out$FDR < 0.05), \n                 c(\"seqnames\", \"start\", \"end\", \"strand\", \"Fold\")]\nwrite.table(deseq.bed, file=\"results\/contrast_1_deseq2_sig.bed\", sep=\"\\t\", quote=F, row.names=F, col.names=F)\n<\/pre>\n
\u53c2\u8003\u94fe\u63a5\uff1ahttps:\/\/github.com\/ENCODE-DCC\/atac-seq-pipeline<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u516d\u3001Deeptools\u53ef\u89c6\u5316 #deeptools\u5b89\u88c5conda install deeptools gtf2bed < ~\/gc_genome\/17.Geta\/1.geta\/out.gtf > genome.bed for i in `cat ..\/samples.txt`; do echo “bamCoverage -p 5 –normalizeUsing RPKM -b $i.last.bam -o $i.last.bw”; done > bam2bw.list ParaFly -c bam2bw.list -CPU 9 computeMatrix reference-point –referencePoint TSS -p 15 -b 10000 -a 10000 -R ..\/genome.bed -S ..\/*bw –skipZeros -o matrix1_test_TSS.gz –outFileSortedRegions regions1_test_genes.bed plotHeatmap -m matrix1_test_TSS.gz […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"_links":{"self":[{"href":"http:\/\/www.wuchangsong.com\/index.php?rest_route=\/wp\/v2\/posts\/618"}],"collection":[{"href":"http:\/\/www.wuchangsong.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.wuchangsong.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.wuchangsong.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.wuchangsong.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=618"}],"version-history":[{"count":34,"href":"http:\/\/www.wuchangsong.com\/index.php?rest_route=\/wp\/v2\/posts\/618\/revisions"}],"predecessor-version":[{"id":746,"href":"http:\/\/www.wuchangsong.com\/index.php?rest_route=\/wp\/v2\/posts\/618\/revisions\/746"}],"wp:attachment":[{"href":"http:\/\/www.wuchangsong.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=618"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.wuchangsong.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=618"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.wuchangsong.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=618"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}