Result: KnockoffHybrid: A knockoff framework for hybrid analysis of trio and population designs in genome-wide association studies.

Title:
KnockoffHybrid: A knockoff framework for hybrid analysis of trio and population designs in genome-wide association studies.
Authors:
Yang Y; Department of Biostatistics, City University of Hong Kong, Hong Kong SAR, China; School of Data Science, City University of Hong Kong, Hong Kong SAR, China. Electronic address: yi.yang@cityu.edu.hk., Wang Q; School of Data Science, City University of Hong Kong, Hong Kong SAR, China., Wang C; Department of Biostatistics, Columbia University, New York, NY 10032, USA., Buxbaum J; Departments of Psychiatry, Neuroscience, and Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA., Ionita-Laza I; Department of Biostatistics, Columbia University, New York, NY 10032, USA; Department of Statistics, Lund University, Lund, Sweden.
Source:
American journal of human genetics [Am J Hum Genet] 2024 Jul 11; Vol. 111 (7), pp. 1448-1461. Date of Electronic Publication: 2024 May 30.
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't; Research Support, N.I.H., Extramural
Language:
English
Journal Info:
Publisher: Cell Press Country of Publication: United States NLM ID: 0370475 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1537-6605 (Electronic) Linking ISSN: 00029297 NLM ISO Abbreviation: Am J Hum Genet Subsets: MEDLINE
Imprint Name(s):
Publication: 2008- : [Cambridge, MA] : Cell Press
Original Publication: Baltimore, American Society of Human Genetics.
MeSH Terms:
Genome-Wide Association Study*/methods , Quantitative Trait Loci* , Autism Spectrum Disorder*/genetics , Linkage Disequilibrium*, Humans ; Genetic Predisposition to Disease ; Polymorphism, Single Nucleotide ; Computer Simulation ; Models, Genetic
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Grant Information:
R01 MH095797 United States MH NIMH NIH HHS; R01 MH106910 United States MH NIMH NIH HHS; R01 MH106910 United States MH NIMH NIH HHS
Contributed Indexing:
Keywords: GWAS; TWAS; autism; eQTL; family-based design; hybrid analysis; knockoff statistics; population admixture; population design; statistical genetics
Entry Date(s):
Date Created: 20240531 Date Completed: 20240712 Latest Revision: 20250914
Update Code:
20250915
PubMed Central ID:
PMC11267528
DOI:
10.1016/j.ajhg.2024.05.003
PMID:
38821058
Database:
MEDLINE

Further Information

Both trio and population designs are popular study designs for identifying risk genetic variants in genome-wide association studies (GWASs). The trio design, as a family-based design, is robust to confounding due to population structure, whereas the population design is often more powerful due to larger sample sizes. Here, we propose KnockoffHybrid, a knockoff-based statistical method for hybrid analysis of both the trio and population designs. KnockoffHybrid provides a unified framework that brings together the advantages of both designs and produces powerful hybrid analysis while controlling the false discovery rate (FDR) in the presence of linkage disequilibrium and population structure. Furthermore, KnockoffHybrid has the flexibility to leverage different types of summary statistics for hybrid analyses, including expression quantitative trait loci (eQTL) and GWAS summary statistics. We demonstrate in simulations that KnockoffHybrid offers power gains over non-hybrid methods for the trio and population designs with the same number of cases while controlling the FDR with complex correlation among variants and population structure among subjects. In hybrid analyses of three trio cohorts for autism spectrum disorders (ASDs) from the Autism Speaks MSSNG, Autism Sequencing Consortium, and Autism Genome Project with GWAS summary statistics from the iPSYCH project and eQTL summary statistics from the MetaBrain project, KnockoffHybrid outperforms conventional methods by replicating several known risk genes for ASDs and identifying additional associations with variants in other genes, including the PRAME family genes involved in axon guidance and which may act as common targets for human speech/language evolution and related disorders.
(Copyright © 2024 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Declaration of interests The authors declare no competing interests.