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Efficient estimation of SNP heritability using Gaussian predictive process in large scale cohort studies

With the advent of high throughput genetic data, there have been attempts to estimate heritability from genome-wide SNP data on a cohort of distantly related individuals using linear mixed model (LMM). Fitting such an LMM in a large scale cohort study, however, is tremendously challenging due to its...

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Autores principales: Seal, Souvik, Datta, Abhirup, Basu, Saonli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060362/
https://www.ncbi.nlm.nih.gov/pubmed/35442943
http://dx.doi.org/10.1371/journal.pgen.1010151
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author Seal, Souvik
Datta, Abhirup
Basu, Saonli
author_facet Seal, Souvik
Datta, Abhirup
Basu, Saonli
author_sort Seal, Souvik
collection PubMed
description With the advent of high throughput genetic data, there have been attempts to estimate heritability from genome-wide SNP data on a cohort of distantly related individuals using linear mixed model (LMM). Fitting such an LMM in a large scale cohort study, however, is tremendously challenging due to its high dimensional linear algebraic operations. In this paper, we propose a new method named PredLMM approximating the aforementioned LMM motivated by the concepts of genetic coalescence and Gaussian predictive process. PredLMM has substantially better computational complexity than most of the existing LMM based methods and thus, provides a fast alternative for estimating heritability in large scale cohort studies. Theoretically, we show that under a model of genetic coalescence, the limiting form of our approximation is the celebrated predictive process approximation of large Gaussian process likelihoods that has well-established accuracy standards. We illustrate our approach with extensive simulation studies and use it to estimate the heritability of multiple quantitative traits from the UK Biobank cohort.
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spelling pubmed-90603622022-05-03 Efficient estimation of SNP heritability using Gaussian predictive process in large scale cohort studies Seal, Souvik Datta, Abhirup Basu, Saonli PLoS Genet Methods With the advent of high throughput genetic data, there have been attempts to estimate heritability from genome-wide SNP data on a cohort of distantly related individuals using linear mixed model (LMM). Fitting such an LMM in a large scale cohort study, however, is tremendously challenging due to its high dimensional linear algebraic operations. In this paper, we propose a new method named PredLMM approximating the aforementioned LMM motivated by the concepts of genetic coalescence and Gaussian predictive process. PredLMM has substantially better computational complexity than most of the existing LMM based methods and thus, provides a fast alternative for estimating heritability in large scale cohort studies. Theoretically, we show that under a model of genetic coalescence, the limiting form of our approximation is the celebrated predictive process approximation of large Gaussian process likelihoods that has well-established accuracy standards. We illustrate our approach with extensive simulation studies and use it to estimate the heritability of multiple quantitative traits from the UK Biobank cohort. Public Library of Science 2022-04-20 /pmc/articles/PMC9060362/ /pubmed/35442943 http://dx.doi.org/10.1371/journal.pgen.1010151 Text en © 2022 Seal et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Methods
Seal, Souvik
Datta, Abhirup
Basu, Saonli
Efficient estimation of SNP heritability using Gaussian predictive process in large scale cohort studies
title Efficient estimation of SNP heritability using Gaussian predictive process in large scale cohort studies
title_full Efficient estimation of SNP heritability using Gaussian predictive process in large scale cohort studies
title_fullStr Efficient estimation of SNP heritability using Gaussian predictive process in large scale cohort studies
title_full_unstemmed Efficient estimation of SNP heritability using Gaussian predictive process in large scale cohort studies
title_short Efficient estimation of SNP heritability using Gaussian predictive process in large scale cohort studies
title_sort efficient estimation of snp heritability using gaussian predictive process in large scale cohort studies
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060362/
https://www.ncbi.nlm.nih.gov/pubmed/35442943
http://dx.doi.org/10.1371/journal.pgen.1010151
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