Previous work on partitioning SNP-heritability has used restricted maximum likelihood (REML) as implemented in GCTA [1, 11–14]. REML requires individual genotypes, but many of the largest GWAS analyses are conducted through meta-analysis of study-specific results, and so typically only summary statistics, not individual genotypes, are available for these studies. Even when individual genotypes are available, using REML to analyze multiple functional categories becomes computationally intractable at sample sizes in the tens of thousands. Here, we introduce a method for partitioning heritability, stratified LD score regression, that requires only GWAS summary statistics and LD information from an external reference panel that matches the population studied in the GWAS.
