homer 处理HiC-pro的结果

写在前面，得到HiC-pro的结果后，我们想看看显著的互作区域以及两个样本互作区域的不同.

1. 关注正常染色体

awk -F "\t" '{if ($2!="chloroplast" && $2!="mitochondria" && $2!~ "^ctg" && $5!~ "^ctg" && $5!="chloroplast" && $5!="mitochondria") {print $0}}' hic-pro8result > result_noChrCM.homer

2. 比较不同实验组数据大小，如果相差比较大，利用shuf随机提取等量数据
   例如

wc -l *homer

  33444357 HiC_S8.allValidPairs
  19227356 HiC_S7.allValidPairs

利用shuf提取

shuf -n 19227356 HiC_S8.allValidPairs > shuf_HiC_S8.allValidPairs

3. homer处理第一步 makeTagDirectory

makeTagDirectory S8output-directory -format HiCsummary shuf_HiC_S8.allValidPairs -tbp 1
makeTagDirectory S7output-directory -format HiCsummary HiC_S7.allValidPairs -tbp 1

3.1 再次 make TagDirectory

cp -r S7output-directory S7output-directory_processed
cp -r S8output-directory S8output-directory_processed
makeTagDirectory S7output-directory_processed -update -restrictionSite GATC -removeSelfLigation -removePEbg -genome ref.fasta -removeSpikes 10000 5

4. homer 得到 interactions 区域

analyzeHiC S7output-directory_processed -res 2000 -superRes 2000 -minDist 1000 -pvalue 0.05 -nomatrix -cpu 16 -interactions S7_2K_p005.txt

5. 比较两个实验不同互作区域

analyzeHiC  S8output-directory_processed/ -res 5000 -ped S7output-directory_processed/ -interactions S8_VS_S7_significantInteractions.txt -nomatrix

6. 得到结果之后我们想实现可视化，按照washu官网进行操作--https://epigenomegateway.readthedocs.io/en/latest/tracks.html?highlight=tbi#prepare-track-files

for i in ./*txt; do awk 'BEGIN{FS=OFS="\t"}{print $3,$4,$5,$9":"$10"-"$11","$17}' $i > `basename $i`_washu; done

for i in ./washu_*; do sort -k1,1 -k2,2n $i > sorted_`basename $i`; done

for i in ./sorted_washu_*; do bgzip -c $i > `basename $i`.gz;done

 for i in ./*gz; do tabix -p bed $i ; done

HiC.jpg

还有更多功能参考官网、http://homer.ucsd.edu/homer/interactions/

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更新，有时候被迫移动了安装路径，程序报错，可以使用

perl  configureHomer.pl -install homer

快速重新安装一下