| I live in this field, as a computer scientist learning the biology, and trying to make a living with a bootstrapped company. I wrote a post about why GATK - one of the most popular bioinformatic tools in Next Generation Sequencing should not be put into a clinical pipeline: http://blog.goldenhelix.com/?p=1534 In terms of your ideal software strategy, I can speak to that as well, as I am actually attempting to do almost exactly what you suggesting. My team is all masters in CS & Stats, with focus on kick-ass CG visualization and UX. We released a free genome browser (visualization of NGS data and public annotations) that reflects this: http://www.goldenhelix.com/GenomeBrowse/ But you're right, selling software in this field is a very weird thing. It's almost B2B, but academics are not businesses and their alternative is always to throw more Post-Doc man-power at the problem or slog it out with open source tools (which many do). That said, we've been building our business (in Montana) over the last 10 years through the GWAS era selling statistical software and are looking optimistically into the era of sequencing having a huge impact on health care. |
I've seen you link to your blog post a couple of times now, and I still think it's misleading. I do wonder whether your conflict of interest (selling competing software) has led you to come to a pretty unreasonable conclusion. (My conflict of interest is that I have a Broad affiliation, though I'm not a GATK developer.)
In your blog post, you received output from 23andme. The GATK was part of the processing pipeline that they used. What you received from 23andme indicated that you had a loss of function indel in a gene. However, it turns out that upon re-analysis, that was not present in your genome; it was just present in the genome of someone else processed at the same time as you.
Somehow, the conclusion that you draw is that the GATK should not be used in a clinical pipeline. This is hugely problematic:
1) It's not clear that there were any errors made by the GATK. Someone at 23andme said it was a GATK error, but the difference between "user error" and "software error" can be blurred for advantage. It's open source, so can someone demonstrate where this bug was fixed, if it ever existed?
2) Now let's assume that there was truly a bug. Is it not the job of the entity using the software to check it to ensure quality? An appropriate suite of test data would surely have caught this error yielding the wrong output. Wouldn't it be as fair, if not more so, to say that 23andme should not be used for clinical purposes since they don't do a good job of paying attention to their output?
Your blog post shows, for sure, a failure at 23andme. Depending on whether the erroneous output was purely due to 23andme or if the GATK had a bug in production code, your post shows an interesting system failure: an alignment of mistakes at 23andme and in the GATK. But I really don't think it remotely supports the argument that the GATK is unsuitable for use in a clinical sequencing pipeline.