Warning, the concept of the heritability model is quite complicated; it took me about nine years to understand!
All heritability analyses begin by specifying a heritability model, which describes how much each SNP is expected to influence the phenotype. We have shown that for many analyses, the choice of heritability model is very important. For example, changing the heritability model can lead to very different estimates of SNP heritability and heritability enrichments.
The first heritability analyses used the GCTA Model, which assumes that all SNP contributes equally. Since then, many different models have been developed, that try to more accurately describe how heritability varies across the genome. For example, we proposed the LDAK Model, where the expected heritability contributed by a SNP depends on its MAF and local levels of linkage disequilibrium (LD).
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In our paper Evaluating and improving heritability models using summary statistics (Nature Genetics, 2020), we developed a method for measuring how well heritability models fit real data. We used this method to compare 12 different heritability models across a wide range of complex traits. When we restricted to simple heritability models, the best-performing was the LDAK-Thin Model, which is an improved version of the LDAK Model. When we considered all models, the BLD-LDAK Model performed best, a model where the expected heritability contributed by a SNP depends on its MAF, LD and functional annotations.
Recommendations:
When using individual-level data, it is necessary to use a simple heritability model, so we recommend using the LDAK-Thin Model. When performing heritability analysis using summary statistics, it is feasible to use complex heritability models, so we recommend using the BLD-LDAK Model. Note that the BLD-LDAK Model can only be used with human data, so if using non-human data, you should always use the LDAK-Thin Model.
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Technical Details describes how to implement different models, while Comparing Models explains how you can use LDAK to test different heritability models.
