Abstract
SNP heritability, the proportion of phenotypic variance explained by SNPs, has been reported for many hundreds of traits. Its estimation requires strong prior assumptions about the distribution of heritability across the genome, but current assumptions have not been thoroughly tested. By analyzing imputed data for a large number of human traits, we empirically derive a model that more accurately describes how heritability varies with minor allele frequency (MAF), linkage disequilibrium (LD) and genotype certainty. Across 19 traits, our improved model leads to estimates of common SNP heritability on average 43% (s.d. 3%) higher than those obtained from the widely used software GCTA and 25% (s.d. 2%) higher than those from the recently proposed extension GCTA-LDMS. Previously, DNase I hypersensitivity sites were reported to explain 79% of SNP heritability; using our improved heritability model, their estimated contribution is only 24%.
| Original language | English |
|---|---|
| Pages (from-to) | 986-992 |
| Number of pages | 7 |
| Journal | Nature Genetics |
| Volume | 49 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 2017 |
| Externally published | Yes |
Keywords
- Alleles
- Case-Control Studies
- Chromosome Fragile Sites
- Cohort Studies
- Computer Simulation
- Deoxyribonuclease I
- Gene Frequency
- Genetic Association Studies
- Genome-Wide Association Study/methods
- Humans
- Inheritance Patterns
- Models, Genetic
- Multifactorial Inheritance/genetics
- Polymorphism, Single Nucleotide/genetics
- Quantitative Trait, Heritable