General Kernel Machine Methods for Multi-Omics Integration and Genome-Wide Association Testing With Related Individuals.

doi:10.1002/gepi.22610

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General Kernel Machine Methods for Multi-Omics Integration and Genome-Wide Association Testing With Related Individuals.

Genetic epidemiology - 1 Jan 2025

Little Amarise, Zhao Ni, Mikhaylova Anna, Zhang Angela, Ling Wodan, Thibord Florian, Johnson Andrew D, Raffield Laura M, Curran Joanne E, Blangero John, O'Connell Jeffrey R, Xu Huichun, Rotter Jerome I, Rich Stephen S, Rice Kenneth M, Chen Ming-Huei, Reiner Alexander, Kooperberg Charles, Vu Thao, Hou Lifang, Fornage Myriam, Loos Ruth J F, Kenny Eimear, Mathias Rasika, Becker Lewis, Smith Albert V, Boerwinkle Eric, Yu Bing, Thornton Timothy, Wu Michael C

Abstract excerpt

Integrating multi-omics data may help researchers understand the genetic underpinnings of complex traits and diseases. However, the best ways to integrate multi-omics data and use them to address pressing scientific questions remain a challenge. One important and topical problem is how to assess the aggregate effect of multiple genomic data types (e.g. genotypes and gene expression levels) on a phenotype,...

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PMID: 39812506
DOI: 10.1002/gepi.22610
PMCID: PMC13170581

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