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GWAS Study

Iterative hard thresholding in genome-wide association studies: Generalized linear models, prior weights, and double sparsity.

Chu BB, Keys KL, German CA et al.

32491161 PubMed ID
GWAS Study Type
185565 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

CB
Chu BB
KK
Keys KL
GC
German CA
ZH
Zhou H
ZJ
Zhou JJ
SE
Sobel EM
SJ
Sinsheimer JS
LK
Lange K
Chapter II

Abstract

Summary of the research findings

Consecutive testing of single nucleotide polymorphisms (SNPs) is usually employed to identify genetic variants associated with complex traits. Ideally one should model all covariates in unison, but most existing analysis methods for genome-wide association studies (GWAS) perform only univariate regression.

185,565 European ancestry individuals

Chapter III

Study Statistics

Key metrics and study information

185565
Total Participants
GWAS
Study Type
No
Replicated
European
Ancestry
Chapter IV

AI-Generated Summary

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