1. deeptools可视化

将bdg文件转为bw文件

ls *treat_pileup.bdg | while read id;dosample=${id%%_*}bedGraphToBigWig ${sample}_treat_pileup.bdg ~/my_data/ref_data/mouse/fasta/mm10.chrom.sizes ../bw/${sample}.bwdone

查看TSS附件信号强度：

cat >tss.shls *.bw | while read iddosample=${id%.*}computeMatrix reference-point  --referencePoint TSS  -p 15  -S ${sample}.bw -b 10000 -a 10000 -R ~/my_data/ref_data/mouse/fasta/mm10.tss.bed --missingDataAsZero --skipZeros  -o ../tss/${sample}_TSS.gz  donenohup sh tss.sh &##     both plotHeatmap and plotProfile will use the output from   computeMatrixls *.gz | while read iddosample=${id%.*}plotHeatmap -m ${sample}.gz  --colorMap RdYlBu_r -out ${sample}_Heatmap.pngplotHeatmap -m ${sample}.gz   --colorMap RdYlBu_r -out ${sample}_Heatmap.pdf --plotFileFormat pdf  --dpi 720  plotProfile -m ${sample}.gz  -out ${sample}_plotProfile.pngplotProfile -m ${sample}.gz  -out ${sample}_plotProfile.pdf --plotFileFormat pdf --perGroup --dpi 720 done

2-cell-1_TSS_Heatmap.png

查看基因body的信号强度

ls *.bw | while read iddosample=${id%.*}computeMatrix scale-regions  -p 15  \-S ${sample}.bw -b 10000 -a 10000 -R ~/my_data/ref_data/mouse/fasta/mm10.tss.bed  --missingDataAsZero --skipZeros  -o ../tss/${sample}_TSS.gz  done#可视化ls *.gz | while read iddosample=${id%.*}plotHeatmap -m ${sample}.gz  --colorMap RdYlBu_r -out ${sample}_Heatmap.pngplotHeatmap -m ${sample}.gz   --colorMap RdYlBu_r -out ${sample}_Heatmap.pdf --plotFileFormat pdf  --dpi 720  plotProfile -m ${sample}.gz  -out ${sample}_plotProfile.pngplotProfile -m ${sample}.gz  -out ${sample}_plotProfile.pdf --plotFileFormat pdf --perGroup --dpi 720 done

2.peaks注释

主要用Y叔的R包ChIPseeker对peaks的位置（如peaks位置落在启动子、UTR、内含子等）以及peaks临近基因的注释。

# 下载老鼠的基因和lincRNA的TxDb对象，#安装所需R包if (!require("BiocManager", quietly = TRUE))    install.packages("BiocManager")BiocManager::install("TxDb.Mmusculus.UCSC.mm10.knownGene")BiocManager::install("org.Mm.eg.db")#载入各种包library("ChIPseeker")library(clusterProfiler)library("org.Mm.eg.db")library(TxDb.Mmusculus.UCSC.mm10.knownGene)txdb <- TxDb.Mmusculus.UCSC.mm10.knownGene#函数readPeakFile读入summit.bed文件bedfile <- readPeakFile("2-cell-1_summits.bed")#注释peakspeakAnnoList <- annotatePeak(bedfile, tssRegion=c(-5000, 5000), TxDb=txdb, annoDb="org.Mm.eg.db")promoter <- getPromoters(TxDb=txdb, upstream=3000, downstream=3000)tagMatrix <- getTagMatrix(bedfile, windows=promoter) # 然后查看这些peaks在所有基因的启动子附近的分布情况，热图模式tagHeatmap(tagMatrix, xlim=c(-3000, 3000), color="red")# 然后查看这些peaks在所有基因的启动子附近的分布情况，信号强度曲线图plotAvgProf(tagMatrix, xlim=c(-3000, 3000),             xlab="Genomic Region (5'->3')", ylab = "Read Count Frequency")

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可视化,展示peak在基因组特征区域的分布以及转录因子在TSS区域的结合。

library(ggplot2)#饼图plotAnnoPie(peakAnnoList)plotDistToTSS(peakAnnoList,title="Distribution of transcription factor-binding loci relative to TSS")#covplot函数可以直接接受macs2-callpeak的输出bed文件进行画图。#函数返回的图中，每个竖线表示一个peaks在染色体的位置，线的宽度表示peaks在染色体的分布范围。covplot(bedfile)

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