Accurate and equitable medical genomic analysis requires an understanding of demography and its influence on sample size and ratio

Genome Biol. 2017 Feb 27;18(1):42. doi: 10.1186/s13059-017-1172-8.

Abstract

In a recent study, Petrovski and Goldstein reported that (non-Finnish) Europeans have significantly fewer nonsynonymous singletons in Online Mendelian Inheritance in Man (OMIM) disease genes compared with Africans, Latinos, South Asians, East Asians, and other unassigned non-Europeans. We use simulations of Exome Aggregation Consortium (ExAC) data to show that sample size and ratio interact to influence the number of these singletons identified in a cohort. These interactions are different across ancestries and can lead to the same number of identified singletons in both Europeans and non-Europeans without an equal number of samples. We conclude that there is a need to account for the ancestry-specific influence of demography on genomic architecture and rare variant analysis in order to address inequalities in medical genomic analysis.The authors of the original article were invited to submit a response, but declined to do so. Please see related Open Letter: http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1016-y.

Publication types

  • Letter
  • Comment

MeSH terms

  • Demography*
  • Ethnicity
  • Genomics / methods*
  • Genomics / standards*
  • Humans
  • Reproducibility of Results
  • Sample Size*