I use RSEM to count abundance of each transcript after alignment with STAR and featureCounts to count abundance of each transcript after alignment with Bowtie.
My question is, if a read map on a given location of the genome, but at this location, there are multiple transcripts overlapping : How RSEM or featureCounts decide which transcript is it ?
For example, in the mouse at this location : https://www.ensembl.org/Mus_musculus/Location/View?r=7:44804176-44853021;db=core;g=ENSMUSG00000074141
You can see il4i1 and nup62 are overlapping.
But in my counts table, I have a big difference between abundances of those 2 genes. Why ?
3 answers
Mapping to the transcriptome will result in a high rate of reads mapping to multiple locations, due to the multiple isoforms present in a transcriptome. RSEM will use an expectation-maximization to optimally assign (fractional) counts from multi-mapping reads, while featureCounts will, with default settings, discard all multi-mapping reads.
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