You can ‘go with the original supposition of cheap and fast readout of whole genomes being available’, but in that case the counterargument is malformed—it’s way cheaper than it was, but still way too expensive for monumentally massive replication, so failure to have done so is still expected.
So, what can you do once you have it super-cheap? The main thing to do is to do a huge association fishing-expedition studies, with the enormous numbers being sufficient to make up for the huge numbers of hypotheses being tested, which then lead into studies to determine the nature of the association. The HGP tested what? A few dozen people? That’s not going to be statistically significant for just about anything.
When the genome gets cheap enough that it’s insignificant compared to the other costs, then it changes the cost analysis for ordinary experiment design in two ways. First, you can add genomic data to existing experiments just to clarify the controls. Secondly, in genomic experiments, it enables you to expand your cohort. This in turn shifts cost-saving focus to the other per-person elements. An experiment could take, say, the full genome, an online IQ test, and several proxies for intelligence, and sample many people, rather than do multiple batteries of IQ tests conducted in person. If a genome costs $5, you can afford to have a cohort that will make the experiment worth something. If a genome costs $1k, you’re not going to be able to afford the massive replication, no matter how cheap you make the profiling. Even if you maintain your profiling standards, saving that much money will let you expand your cohort.
You can ‘go with the original supposition of cheap and fast readout of whole genomes being available’, but in that case the counterargument is malformed—it’s way cheaper than it was, but still way too expensive for monumentally massive replication, so failure to have done so is still expected.
So, what can you do once you have it super-cheap? The main thing to do is to do a huge association fishing-expedition studies, with the enormous numbers being sufficient to make up for the huge numbers of hypotheses being tested, which then lead into studies to determine the nature of the association. The HGP tested what? A few dozen people? That’s not going to be statistically significant for just about anything.
When the genome gets cheap enough that it’s insignificant compared to the other costs, then it changes the cost analysis for ordinary experiment design in two ways. First, you can add genomic data to existing experiments just to clarify the controls. Secondly, in genomic experiments, it enables you to expand your cohort. This in turn shifts cost-saving focus to the other per-person elements. An experiment could take, say, the full genome, an online IQ test, and several proxies for intelligence, and sample many people, rather than do multiple batteries of IQ tests conducted in person. If a genome costs $5, you can afford to have a cohort that will make the experiment worth something. If a genome costs $1k, you’re not going to be able to afford the massive replication, no matter how cheap you make the profiling. Even if you maintain your profiling standards, saving that much money will let you expand your cohort.