| Title: | Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture |
| Journal: | Nature Genetics |
| Published: | 29 Jul 2019 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/31358995/ |
| DOI: | https://doi.org/10.1038/s41588-019-0465-0 |
| URL: | https://europepmc.org/articles/pmc6686906?pdf=render |
Publication 3974
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
SNP-heritability is a fundamental quantity in the study of complex traits. Recent studies have shown that existing methods to estimate genome-wide SNP-heritability can yield biases when their assumptions are violated. While various approaches have been proposed to account for frequency- and linkage disequilibrium (LD)-dependent genetic architectures, it remains unclear which estimates reported in the literature are reliable. Here we show that genome-wide SNP-heritability can be accurately estimated from biobank-scale data irrespective of genetic architecture, without specifying a heritability model or partitioning SNPs by allele frequency and/or LD. We show analytically and through extensive simulations starting from real genotypes (UK Biobank, N = 337 K) that, unlike existing methods, our closed-form estimator is robust across a wide range of architectures. We provide estimates of SNP-heritability for 22 complex traits in the UK Biobank and show that, consistent with our results in simulations, existing biobank-scale methods yield estimates up to 30% different from our theoretically-justified approach.8 Authors
- Kangcheng Hou
- Kathryn S. Burch
- Arunabha Majumdar
- Huwenbo Shi
- Nicholas Mancuso
- Yue Wu
- Sriram Sankararaman
- Bogdan Pasaniuc
Enabling scientific discoveries that improve human health