Hi Shred,
Thanks for your reply! I have some points that I would like to discuss with you further:
Mutect2 isn't designed for RNAseq data at all.
The main reason I favour Mutect2 is that my samples come in pairs, a tumour sample from consenting individuals and a surrounding healthy sample. This may make false-positive results less likely. Do you have any other tool recommendations that can apply matched sample pairs?
A paired end sequencing is done to increase reads confidence, and your analysis voluntarily discards every advantage offered by the paired end design.
I don't understand you. Why do you say my analysis gives up the paired-end advantage? Do you mean switching from paired-end to single-end?
Why not mapping both pair generating a single bam output?
Yes, that's how I did it. But this fails to produce valid variant calling. Suppose we have the following two paired-end seqed mRNAs:
If we treat R1 and R2 separately as single-end RNA-seq, there will be no overlap between the two R1 reads and the two R2 reads. This also means that there would be no potential variant appearing multiple times, which is bad news for variant calling, between these two reads.
and
If keep paired-end data, there will be an overlap between R2a and R1b. This is good news for variant calling between these two reads.
So I always think it is necessary to keep the paired-end form instead of splitting it into two single-end data. But I still haven't found the reason why Mutect2 can't detect any variant using a paired-end BAM file, even though I can visualise a lot of variants using IGV.
I think following GATK Best practices for RNAseq pre-processing (implemented as a NextFlow workflow here ) is a good start point
I found some people use GATK Best practices for RNAseq pre-processing before doing Mutect2. But I don't understand the relationship.
In addition, for paired-end RNA-seq data, Can CalliNGS-NF only process R1 and R2 fastq files sequentially?