美文网首页
2020-07-22

2020-07-22

作者: nvzhang | 来源:发表于2020-07-26 23:36 被阅读0次

    参考文献:The landscape of accessible chromatin in mammalian preimplantation embryos. Nature 2016 Jun 30;534(7609):652-7. PMID: 27309802
    参考教程:https://www.jianshu.com/p/5bce43a537fd
    https://www.jianshu.com/p/09e05bcd6981

    miniconda

    # https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/ 
    wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh
    bash Miniconda3-latest-Linux-x86_64.sh
    source ~/.bashrc 
    #设置镜像。
    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/bioconda
    conda config --set show_channel_urls yes
    #other commands:https://www.jianshu.com/p/a20bb8c0bc5c
    conda  create -n atac -y  python=2
    conda info --envs
    source activate atac
    # 保证所有的软件都是安装在 atac这个环境下面
    conda install -y sra-tools  
    conda install -y trim-galore  samtools bedtools
    conda install -y deeptools homer  meme
    conda install -y macs2 bowtie bowtie2 
    conda install -y  multiqc 
    conda install -y  sambamba
    

    download sra

    #config.sra
    2-cell-1 SRR2927015
    2-cell-2 SRR2927016
    2-cell-4 SRR2927018
    #prefetch
    mkdir {sra,raw,clean,align,peaks,motif,qc}
    cd ../sra 
    source activate atac 
    cat config.sra |while read id;do 
    arr=($id)
    srr=${arr[1]}
    nohup  prefetch $srr & 
    done
    ## 默认下载目录:~/ncbi/public/sra/ 
    

    fastq-dump

    cat config.sra |while read id;
    do arr=($id); srr=${arr[1]}; sample=${arr[0]}
    nohup fastq-dump -A $sample -O ../raw --gzip --split-e ../$srr.sra &
    done
    

    QC

    #config.raw
    ls  ../*_1.fastq.gz > 1 #complete path
    ls  ../*_2.fastq.gz > 2
    paste 1 2 > config.raw
    
    mkdir -p clean 
    cat config.raw  |while read id;
    do echo $id
    arr=($id)
    fq2=${arr[2]}
    fq1=${arr[1]}
    nohup  trim_galore -q 25 --phred33 --length 35 -e 0.1 --stringency 4 --paired -o  clean  $fq1   $fq2  & 
    done 
    
    cd ../qc 
    mkdir -p clean 
    fastqc -t 5  ../clean/2-cell-*gz -o clean 
    mkdir -p raw 
    fastqc -t 5  ../raw/2-cell-*gz -o raw
    

    mapping

    时间有限,只做了前两个数据

    #config.clean
    ls  ../_1*gz >1 
    ls  ../_2*gz >2
    ls ../_1*gz | cut -d"/" -f 6 | cut -d"_" -f 1 >0
    #/home/zhangjianing/nature_2016/clean/2-cell-1_1_val_1.fq.gz
    paste 0 1 2 >config.clean
    cat config.clean |while read id;
    do echo $id; arr=($id); fq2=${arr[2]}; fq1=${arr[1]}; sample=${arr[0]}
    bowtie2  -p 10  --very-sensitive -X 2000 -x  ~/nature_2016/ref/mm10 -1 $fq1 -2 $fq2 |samtools sort  -O bam  -@ 5 -o - > ${sample}.raw.bam 
    samtools index ${sample}.raw.bam 
    bedtools bamtobed -i ${sample}.raw.bam  > ${sample}.raw.bed
    samtools flagstat ${sample}.raw.bam  > ${sample}.raw.stat
    sambamba markdup --overflow-list-size 600000  --tmpdir='./'  -r ${sample}.raw.bam  ${sample}.rmdup.bam
    samtools index   ${sample}.rmdup.bam 
    samtools flagstat  ${sample}.rmdup.bam > ${sample}.rmdup.stat
    
    ##Calculate %mtDNA:( ref:https://www.biostars.org/p/170294/ )
    mtReads=$(samtools idxstats  ${sample}.rmdup.bam | grep 'chrM' | cut -f 3);
    totalReads=$(samtools idxstats  ${sample}.rmdup.bam | awk '{SUM += $3} END {print SUM}')
    echo '==>' ${sample} 'mtDNA Content:' $(bc <<< "scale=2;100*$mtReads/$totalReads")'%'
    
    samtools view  -h  -f 2 -q 30    ${sample}.rmdup.bam   |grep -v chrM |samtools sort  -O bam  -@ 5 -o - > ${sample}.last.bam
    samtools index   ${sample}.last.bam 
    samtools flagstat  ${sample}.la
    st.bam > ${sample}.last.stat 
    bedtools bamtobed -i ${sample}.last.bam  > ${sample}.bed
    done 
    

    peak calling

    ls *.bed | while read id ;
    do macs2 callpeak -t $id  -g mm --nomodel --shift  -100 --extsize 200  -n ${id%%.*} --outdir ../peaks/ ;
    # ${file%%.*}:拿掉第一个 “. ” 及其右边的字符串 (https://blog.csdn.net/chinalinuxzend/article/details/1826623)
    done 
    

    计算插入片段长度

    #config.fraction
    last.bam path/2-cell-1   2-cell-1     
    last.bam path/2-cell-2   2-cell-2     
    #insert_fraction.R
    cmd=commandArgs(trailingOnly=TRUE); 
    input=cmd[1]; output=cmd[2]; 
    a=abs(as.numeric(read.table(input)[,1])); 
    png(file=output);
    hist(a,
    main="Insertion Size distribution",
    ylab="Read Count",xlab="Insert Size",
    xaxt="n",
    breaks=seq(0,max(a),by=10)
    ); 
    axis(side=1,
    at=seq(0,max(a),by=100),
    labels=seq(0,max(a),by=100)
    );
    dev.off() 
    
    cat config.fraction | while read id;
    do arr=($id); input=${arr[0]}; output=${arr[1]}
    samtools view $input.last.bam | cut -f 9 > $output.txt #提取bam文件中的第9列(插入片段长度)
    Rscript insert_fraction.R $output.txt $output.png; 
    done
    
    2-cell-1
    2-cell-2

    FRIP value

    bedtools intersect -a ../new/2-cell-1.bed -b 2-cell-1_peaks.narrowPeak |wc -l
    148928
    wc ../new/2-cell-1.bed
    5105844
    wc ../new/2-cell-1.raw.bed
    5105844
    
    ls *narrowPeak|while  read id;
    do 
    echo $id
    bed=../new/$(basename $id "_peaks.narrowPeak").raw.bed
    #ls  -lh $bed 
    Reads=$(bedtools intersect -a $bed -b $id |wc -l|awk '{print $1}')
    totalReads=$(wc -l $bed|awk '{print $1}')
    echo $Reads  $totalReads 
    echo '==> FRiP value:' $(bc <<< "scale=2;100*$Reads/$totalReads")'%'
    done
    

    overlap

    #R studio serve安装失败,改用本地R studio
    library(ChIPseeker)
    library(ChIPpeakAnno)
    setwd("/overlap")
    list.files('./',"*.narrowPeak")
    tmp = lapply(list.files('./',"*.narrowPeak"),function(x){
      return(readPeakFile(file.path('./', x)))
      })
    `2-cell-` <- tmp #更改venn图中的名字,效果不是很好
    ol <- findOverlapsOfPeaks(`2-cell-`[[1]],`2-cell-`[[2]]) 
    png('overlapVenn.png')
    makeVennDiagram(ol)
    dev.off()
    
    overlapVenn

    6.deeptools可视化

    cd /align
    ls *last.bam |while read id;do
    nohup bamCoverage -p 5 --normalizeUsing CPM -b $id -o ${id%%.*}.last.bw & 
    done 
    #TSS附近信号强度
    cd /bw
    ls *.bw | while read id;do
    computeMatrix reference-point  --referencePoint TSS  -p 15  \
    -b 10000 -a 10000    \
    -R /ref/mm10.bed  \
    -S  $id  \
    --skipZeros  -o /TSS/${id%%.*}_TSS.gz  \
    --outFileSortedRegions ${id%%.*}_sortedRegions.bed;
    #plot
    plotHeatmap -m TSS/${id%%.*}_TSS.gz  -out ${id%%.*}_TSS_Heatmap.png
    plotProfile -m TSS/${id%%.*}_TSS.gz  -out ${id%%.*}_TSS_Profile.png
    (plotHeatmap -m ${id%%.*}_TSS.gz  -out ${id%%.*}_TSS_Heatmap.pdf --plotFileFormat pdf  --dpi 720
    plotProfile -m ${id%%.*}_TSS.gz  -out ${id%%.*}_TSS_Profile.pdf --plotFileFormat pdf --perGroup --dpi 720 )
    #gene body 信号强度
    ls *.bw | while read id;do
    computeMatrix scale-regions  -p 15  \
    -R /ref/mm10.bed  \
    -S $id  \
    -b 10000 -a 10000  \
    --skipZeros -o ${id%%.*}_body.gz
    plotHeatmap -m ${id%%.*}_body.gz  -out ${id%%.*}_body_Heatmap.png
    plotProfile -m ${id%%.*}_body.gz  -out ${id%%.*}_body_Profile.png
    
    2-cell-2_TSS_Heatmap.png 2-cell-1_TSS_Heatmap.png

    7.peaks注释

    if (!requireNamespace("BiocManager", quietly = TRUE))
        install.packages("BiocManager")
    BiocManager::install("TxDb.Mmusculus.UCSC.mm10.knownGene")
    if (!requireNamespace("BiocManager", quietly = TRUE))
        install.packages("BiocManager")
    BiocManager::install("org.Mm.eg.db")
    library('CHIPpeakAnno')
    library('TxDb.Mmusculus.UCSC.mm10.knownGene')
    library('clusterProfiler')
    
    setwd("/")
    peakfiles = lapply(list.files('./',"*.bed"),function(x){return(readPeakFile(file.path('./', x)))})
    txdb <- TxDb.Mmusculus.UCSC.mm10.knownGene
    peakAnno <- annotatePeak(peakfiles[[1]],tssRegion=c(-3000, 3000),TxDb=txdb, annoDb="org.Mm.eg.db")
    peakAnno_df <- as.data.frame(peakAnno)
    promoter <- getPromoters(TxDb=txdb, upstream=3000, downstream=3000)
    tagMatrix <- getTagMatrix(peakfiles[[1]], windows=promoter)
    
    # 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")
    
    # 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")
    
    2-cell-1
    #others
    plotAnnoPie(peakAnno)
    plotAnnoBar(peakAnno)
    #peak离最近基因的距离分布
    plotDistToTSS(peakAnno, title="Distribution of transcription factor-binding loci\nrelative to TSS")
    
    图片.png
    图片.png
    图片.png
    #多图展示
    peakAnnoList <- lapply(peakfiles, annotatePeak,TxDb=txdb,tssRegion=c(-3000, 3000))
    plotAnnoBar(peakAnnoList)
    plotDistToTSS(peakAnnoList)
    
    图片.png
    图片.png

    homer peak annotation

    # perl ~/miniconda3/envs/atac/share/homer-4.9.1-5/configureHomer.pl  -install mm10 
    source activate atac
    cd   ../peaks  
    ls *.narrowPeak |while read id;
    do 
    echo $id
    awk '{print $4"\t"$1"\t"$2"\t"$3"\t+"}' $id > ${id%%.*}.homer_peaks.tmp
    annotatePeaks.pl  ${id%%.*}.homer_peaks.tmp mm10  \
    1>${id%%.*}.peakAnn.xls \
    2>${id%%.*}.annLog.txt
    done
    

    motifs

    ls ../*.tmp |while read id;
    do  findMotifsGenome.pl $id mm10 ${id%%.*}_motifDir -len 8,10,12  
    done
    
    图片.png

    相关文章

      网友评论

          本文标题:2020-07-22

          本文链接:https://www.haomeiwen.com/subject/xsqtlktx.html