| Title: | BIGFAM - variance components analysis from relatives without genotype |
| Journal: | Nature Communications |
| Published: | 1 Jul 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40593523/ |
| DOI: | https://doi.org/10.1038/s41467-025-60502-0 |
| URL: | https://www.nature.com/articles/s41467-025-60502-0.pdf |
Publication 16387
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Abstract
Estimating variance components of phenotypes provides a fundamental basis for understanding complex traits. However, most existing methods require genotype data, which is costly to obtain and often unavailable, limiting their scalability. To address this limitation, we developed BIGFAM, a genotype-free framework that estimates variance components by genetic, shared environmental, and X chromosome effects using only phenotype data from relative pairs. We analyze variance components in Generation Scotland and UK Biobank datasets and demonstrate that BIGFAM's estimates show high correlation with genotype-based methods (r$$r$$ = 0.85 for heritability and 0.64 for X chromosome components). We identify strong nuclear-family-specific shared environmental effects in dietary-related phenotypes. These results establish a new approach for analyzing variance components across diverse populations without the need for genetic data.</p>
11 Keywords
- Biological Specimen Banks
- Chromosomes, Human, X
- Female
- Genome, Human
- Genotype
- Humans
- Male
- Models, Genetic
- Phenotype
- Scotland
- United Kingdom
2 Authors
- Jaeeun Jerry Lee
- Buhm Han
1 Application
| Application ID | Title |
|---|---|
| 285388 | Development of a Statistical Method for heritability for X Chromosome Inactivation |
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