MARS: leveraging allelic heterogeneity to increase power of association testing

MARS: leveraging allelic heterogeneity to increase power of association testing

Abstract In standard genome-wide association studies (GWAS), the standard association test is underpowered to detect associations between loci with multiple causal variants with small effect sizes. We propose a statistical method, Model-based Association test Reflecting causal Status (MARS), that fi...

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Main Authors: Farhad Hormozdiari, Junghyun Jung, Eleazar Eskin, Jong Wha J. Joo
Format: Article
Language:English
Published: BMC 2021-04-01
Series:Genome Biology
Subjects:
Association studies
Causal variants
Set-based association analysis
Online Access:https://doi.org/10.1186/s13059-021-02353-8
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spelling doaj-1e301c80dcd74ee2804a25fa2f5673322021-05-02T11:46:50ZengBMCGenome Biology1474-760X2021-04-0122112610.1186/s13059-021-02353-8MARS: leveraging allelic heterogeneity to increase power of association testingFarhad Hormozdiari0Junghyun Jung1Eleazar Eskin2Jong Wha J. Joo3Department of Epidemiology, Harvard T.H. Chan School of Public HealthDepartment of Life Science, Dongguk University-SeoulDepartment of Computer Science, University of California, Los AngelesDepartment of Computer Science and Engineering, Dongguk University-SeoulAbstract In standard genome-wide association studies (GWAS), the standard association test is underpowered to detect associations between loci with multiple causal variants with small effect sizes. We propose a statistical method, Model-based Association test Reflecting causal Status (MARS), that finds associations between variants in risk loci and a phenotype, considering the causal status of variants, only requiring the existing summary statistics to detect associated risk loci. Utilizing extensive simulated data and real data, we show that MARS increases the power of detecting true associated risk loci compared to previous approaches that consider multiple variants, while controlling the type I error.https://doi.org/10.1186/s13059-021-02353-8Association studiesCausal variantsSet-based association analysis
collection DOAJ
language English
format Article
sources DOAJ
author Farhad Hormozdiari
Junghyun Jung
Eleazar Eskin
Jong Wha J. Joo
spellingShingle Farhad Hormozdiari
Junghyun Jung
Eleazar Eskin
Jong Wha J. Joo
MARS: leveraging allelic heterogeneity to increase power of association testing
Genome Biology
Association studies
Causal variants
Set-based association analysis
author_facet Farhad Hormozdiari
Junghyun Jung
Eleazar Eskin
Jong Wha J. Joo
author_sort Farhad Hormozdiari
title MARS: leveraging allelic heterogeneity to increase power of association testing
title_short MARS: leveraging allelic heterogeneity to increase power of association testing
title_full MARS: leveraging allelic heterogeneity to increase power of association testing
title_fullStr MARS: leveraging allelic heterogeneity to increase power of association testing
title_full_unstemmed MARS: leveraging allelic heterogeneity to increase power of association testing
title_sort mars: leveraging allelic heterogeneity to increase power of association testing
publisher BMC
series Genome Biology
issn 1474-760X
publishDate 2021-04-01
description Abstract In standard genome-wide association studies (GWAS), the standard association test is underpowered to detect associations between loci with multiple causal variants with small effect sizes. We propose a statistical method, Model-based Association test Reflecting causal Status (MARS), that finds associations between variants in risk loci and a phenotype, considering the causal status of variants, only requiring the existing summary statistics to detect associated risk loci. Utilizing extensive simulated data and real data, we show that MARS increases the power of detecting true associated risk loci compared to previous approaches that consider multiple variants, while controlling the type I error.
topic Association studies
Causal variants
Set-based association analysis
url https://doi.org/10.1186/s13059-021-02353-8
work_keys_str_mv AT farhadhormozdiari marsleveragingallelicheterogeneitytoincreasepowerofassociationtesting
AT junghyunjung marsleveragingallelicheterogeneitytoincreasepowerofassociationtesting
AT eleazareskin marsleveragingallelicheterogeneitytoincreasepowerofassociationtesting
AT jongwhajjoo marsleveragingallelicheterogeneitytoincreasepowerofassociationtesting
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