| Title: | Accurate and efficient estimation of local heritability using summary statistics and the linkage disequilibrium matrix |
| Journal: | Nature Communications |
| Published: | 2 Dec 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38040712/ |
| DOI: | https://doi.org/10.1038/s41467-023-43565-9 |
| URL: | https://www.nature.com/articles/s41467-023-43565-9.pdf |
| Citations: | 1 (1 in last 2 years) as of 8 Aug 2024 |
Publication 9242
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Abstract
Existing SNP-heritability estimators that leverage summary statistics from genome-wide association studies (GWAS) are much less efficient (i.e., have larger standard errors) than the restricted maximum likelihood (REML) estimators which require access to individual-level data. We introduce a new method for local heritability estimation - Heritability Estimation with high Efficiency using LD and association Summary Statistics (HEELS) - that significantly improves the statistical efficiency of summary-statistics-based heritability estimator and attains comparable statistical efficiency as REML (with a relative statistical efficiency >92%). Moreover, we propose representing the empirical LD matrix as the sum of a low-rank matrix and a banded matrix. We show that this way of modeling the LD can not only reduce the storage and memory cost, but also improve the computational efficiency of heritability estimation. We demonstrate the statistical efficiency of HEELS and the advantages of our proposed LD approximation strategies both in simulations and through empirical analyses of the UK Biobank data.</p>
3 Authors
- Hui Li
- Rahul Mazumder
- Xihong Lin
1 Application
| Application ID | Title |
|---|---|
| 52008 | Development of statistical methods to discover novel genetic associations, explain underlying biological mechanisms, and develop risk prediction models across varied complex diseases. |
Enabling scientific discoveries that improve human health