Shifting perspectives on our WGS and lower sample numbers focus

Increasingly, we are seeing the genetic field slowly pivot toward the path we at GI have insisted on (and blazed) all along. Namely, 1) whole genome (WGS) instead of whole exome (WES) and 2) well characterized cohorts (which can mean smaller number of samples) instead of larger and larger studies.

Shifting perspectives on our WGS and lower sample numbers focus

Increasingly, we are seeing the genetic field slowly pivot toward the path we at Genetic Intelligence have insisted on (and blazed) all along. Namely, 1) whole genome (WGS) instead of whole exome (WES) and 2) well characterized cohorts(which can mean smaller number of samples) instead of larger and larger studies. We are excited to see this development.

1) While the zeigeist shuned WGS analysis because of its inherent noise and thus great difficulty, we embraced the WGS challenge from the inception of Genetic Intelligence because it is unavoidable on the way to achieving genomic cipher. This recent Cell paper agrees, writing that:

WGS will be a predominant technology for genetic analysis fundamental change compared to previous decades  have relied on genetic markers that are indirect proxies  only from the exonic regions of the genome

2) On our critical point that more and more WES data is not the answer, and that we have to be able to find causal genetic features using a lower number of samples, there was this kernel in another Cell paper of the same series:

we are skeptical of the marginal value of ever-larger studies

Next comes the question of how to effectively achieve these two features, which are critical if precision medicine is to succeed. And we are here with the solution.