Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics.

ABSTRACT: Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an

SUBMITTER: Williams CM 

PROVIDER: S-EPMC10584908 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature