3 citations · 3 across the 2 of their papers we have counts for
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stat.ME2023
A statistical framework for GWAS of high dimensional phenotypes using summary statistics, with application to metabolite GWAS
Weiqiong Huang, Emily C. Hector, Joshua Cape +1
The recent explosion of genetic and high dimensional biobank and 'omic' data has provided researchers with the opportunity to investigate the shared genetic origin (pleiotropy) of…
stat.ME2018★ 3 cited
Accounting for unobserved covariates with varying degrees of estimability in high dimensional biological data
Chris McKennan, Dan Nicolae
An important phenomenon in high dimensional biological data is the presence of unobserved covariates that can have a significant impact on the measured response. When these factors…