I'm interested about your opinion on how often and when do you use, or don't use the visualization of individual reads from NGS. Or whether you most of the time just view the "piled-up" depictions (sometimes called "coverage") of the data.
Would it suffice, to you, to have only the "piled-up" representation for experiments such RNAseq, Chip-seq, xxx-Seq type of experiment?
I'm not talking about the consensus sequence.
As in the following example, I'm interested, how often you find more helpful to look in the "hills" (row under the blue annotation), or the gray "lines" reads with mismatches highlighted in color.
The core concept for DeepVariant comes from how human scientists look at a putative variant in a genome browser like IGV, evaluating the evidence: How many reads support the variant? Do the reads have good base and mapping quality scores? Are there any unexpected patterns in read mapping or other variants nearby?
Can you elaborate how you intend to generate that "piled-up" representation? Would that be a consensus sequence? At the end of the day no one practically looks at individual/single reads but people do look at individual reads when they are piling up in a location/gene etc when making decisions about SNP's etc.
98% of the time I just look at the coverage but once in a while, it is quite useful to have the individual reads as well.