SNP‐based heritability and selection analyses: Improved models and new results. (13th March 2022) - Speed, Doug; Kaphle, Anubhav; Balding, David J.
Abstract: Complex‐trait genetics has advanced dramatically through methods to estimate the heritability tagged by SNPs, both genome‐wide and in genomic regions of interest such as those defined by functional annotations. The models underlying many of these analyses are inadequate, and consequently many SNP‐heritability results published to date are inaccurate. Here, we review the modelling issues, both for analyses based on individual genotype data and association test statistics, highlighting the role of a low‐dimensional model for the heritability of each SNP. We use state‐of‐art models to present updated results about how heritability is distributed with respect to functional annotations in the human genome, and how it varies with allele frequency, which can reflect purifying selection. Our results give finer detail to the picture that has emerged in recent years of complex trait heritability widely dispersed across the genome. Confounding due to population structure remains a problem that summary statistic analyses cannot reliably overcome. Also see the video abstract here: https://youtu.be/WC2u03V65MQ Abstract : We review progress in SNP‐heritability analyses, addressing the problems of 'too many predictors' and complex LD in statistical models that incorporate properties of SNP context. We present new results from state‐of‐art models about how the heritability of human traits is distributed across the genome, and about purifying selection.