Re:All Those 23andMe Spit Tests Were Part of a Bigger Plan
by farresito on Monday November 08, 2021 @03:01PM
(#29153522)
The issue with SNPs is that they are generally common in the population, and a variant that is common will rarely have a big effect. If we look at GWAS studies, most of them do not explain much of the variance of a phenotype. It either is due to environment/epigenetics or we are not using the right data. Part of it is of course the former, but I'm betting on the latter. I'm not a researcher, so I could of course be very wrong.
Re:All Those 23andMe Spit Tests Were Part of a Bigger Plan
by mbreese on Tuesday November 09, 2021 @12:15AM
(#29157991)
There is a difference in scale. For the research 23andme wants to do, they need to identify variants that occur in a significant part of the population (~1% or so). They need to do this because any potential drug/treatment would have to be developed for a big enough patient pool. Large population level genome studies like 1000 genomes and NIH All of Us studies are all aimed at finding those ~1% variants.
But if you’re looking for what is going on in an individual, then yes… SNP chip data isn’t as informative as whole genome (or exome) sequencing.
Re:All Those 23andMe Spit Tests Were Part of a Bigger Plan
by ernst_10 on Monday November 08, 2021 @02:46PM
(#29153378)
If most data is common between people, then storing the diffs should be cheap.
Re:All Those 23andMe Spit Tests Were Part of a Bigger Plan
by mbreese on Tuesday November 09, 2021 @12:05AM
(#29157939)
It still costs a lot to process and until it’s all aligned, you don’t know which parts are common. So, even if you have smaller long term storage, whole genome data still has significantly more costs to work with (at least an order of magnitude, if not two).
And you store more information than just the raw sequence (quality scores, multiple reads, etc).
For most of the tests that 23andme would want to run on a population, like risk assessment, you don’t get much more information from whole genome vs arrays. And the extra data (and noise) you get from whole genome can make association studies significantly more difficult.
Also with whole genomes, the extra cost in sequencing, storage, and processing time (all of which are significantly higher) wouldn’t be worth it from a cost/benefit point of view. Remember, most of the data is redundant or common between people, so full sequencing is really only beneficial in specific scenarios.