ArticlePLoS genetics2022
Efficient estimation of SNP heritability using Gaussian predictive process in large scale cohort studies.
Article in PLoS genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Heritability, phenotypic, and genetic correlations across dimensional and categorical models of bipolar disorder in a family sample.Journal of affective disorders · 2025Article
- Strong Genetic Overlaps Between Dimensional and Categorical Models of Bipolar Disorders in a Family Sample.medRxiv : the preprint server for health sciences · 2024Article
- SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data.PLoS genetics · 2023Article
- Comparing heritability estimators under alternative structures of linkage disequilibrium.G3 (Bethesda, Md.) · 2022Article
- DenVar: density-based variation analysis of multiplex imaging data.Bioinformatics advances · 2022Article
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Authors and funding
3 authors.
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Abstract
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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.