Count ChIP-seq reads across a promoter with featureCounts
When analyzing ChIP-seq data, we sometimes like to focus on promoters as a proxy of gene activation especially for histone marks that are normally associated with gene activation such as H3K9 acetylation or H3K4 tri-methylation.
FeatureCounts has emerged as a competitor to HTSeq and BedTools MultiCov for counting reads across features (ie, exons, genes, promoters). FeatureCounts is great for RNA-seq because it can natively read GTF annotation files, but can't read BED format (that we use a lot in ChIP-seq analysis).
In order to make featureCounts work, we need to extract the TSS coordinates and convert to a BED-like format that it can read (SAF format). In the below script, I extract the positions of the TSSs using a grep search followed by stripping only the neccessary information from the GTF, then using awk and BedTools to expand the region around the TSS by 3kbp.
#!/bin/bash
#Generate an SAF file for TSS intervals from a GTF
#Specify some parameters
GTF=Homo_sapiens.GRCh38.78.gtf
…
FeatureCounts has emerged as a competitor to HTSeq and BedTools MultiCov for counting reads across features (ie, exons, genes, promoters). FeatureCounts is great for RNA-seq because it can natively read GTF annotation files, but can't read BED format (that we use a lot in ChIP-seq analysis).
In order to make featureCounts work, we need to extract the TSS coordinates and convert to a BED-like format that it can read (SAF format). In the below script, I extract the positions of the TSSs using a grep search followed by stripping only the neccessary information from the GTF, then using awk and BedTools to expand the region around the TSS by 3kbp.
#!/bin/bash
#Generate an SAF file for TSS intervals from a GTF
#Specify some parameters
GTF=Homo_sapiens.GRCh38.78.gtf
…