Im trying to run featureCounts to summarize the read counts at exon levels (eg feature level) to assess gene expression levels of different expressed isoforms of a gene. However im a bit uncertain regarding which parameters to use for this purpose such as how to handle with multi-mapping reads and curious with how other people deal with this.
Im using subread v 1.5.0 on paired-end RNAseq data as follows:
featureCounts -p -s 1 -T 5 -f -t exon -g exon_id -a genes.gtf -o counts_output.txt myRNAseqBam.bam
There are additional options such as:
- "-B" (only fragments that have both ends successfully aligned will be considered for summarization)
- "-O" ( reads (or fragments if -p is specifed) will be allowed to be assigned to more than one matched meta-feature (or feature if -f is specifed)
- "-M" (multi-mapping reads/fragments will be counted)
and wondering if people specify these options or not (in the case of paired-end RNA-seq data.).
Is there any best practice for RNA-seq data? Naturally it depends on what you want to do, but here we can assume gene expression quantification at exon level for quantification of expressed isoforms. Also, what is the difference between "-O" and "-M"?