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homer's Introduction

homer

  • 0.Build source
  • 1.homer peak files (R)
  • 2.Perform the bash

0.Build source

Firstly, we create conda source to perform homer analysis.

conda create -n homer
conda activate homer
conda install -c bioconda homer
...  

And then we download the genome files. (It depends on your internet speed.)

perl /home/yangjiajun/miniconda3/envs/homer/share/homer/.//configureHomer.pl -list
perl /home/yangjiajun/miniconda3/envs/homer/share/homer/.//configureHomer.pl -install mm10

1.homer peak files (R)

projPath = "/home/yangjiajun/old/cutcfa/"
load(paste0(projPath, "featurecounts/cut_Anno_df.RData"))

And then we divided the chromatin into promoter regions and gene body regions.

cut%26tag_peak_anno.png

rmdis_bed <- lapply(peakAnno_df[c(1:4,10,11)], function(x){
  x <- x[-grep("Rik$", ignore.case = F, x$SYMBOL),]
  x <- x[grep("Promoter", ignore.case = F, x$annotation), ]
  x <- x[, c(8,1:3)]
  x$Strand <- 0
  colnames(x)[1] <- 'Peak ID'
  return(x)
})

for (i in 1:length(rmdis_bed)) {
  write.table(rmdis_bed[i],
              paste0(projPath, 'homer/', names(rmdis_bed[i]), "_homer.peak"),
              sep = "\t", row.names = F, col.names = F, quote = F)
}

homer_peak_anno.png

2.Perform the bash

vim h1_homer.sh

#!/bin/bash
## Alignment to mm10 ##

cat filenames | while read i; 
do
nohup findMotifsGenome.pl ${i}_homer.peak mm10 MotifOutput_${i}/ -size 200 -mask &
done

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