Genomic-relatedness matrix restricted maximum likelihood (2,24) is a major alternative to LDSC that estimates heritability using raw genotypes among unrelated individuals. While LDSC has the advantage of requiring only summary-level data, and is thus especially applicable to GWAS meta-analysis results, genomic-relatedness matrix restricted maximum likelihood is often considered preferable when raw data are available (25,26) because it is typically found to produce larger SNP-based heritability estimates than those obtained from LDSC (27). One potential explanation for this discrepancy includes the possibility that, because LDSC is typically applied to meta-analytic GWAS data, it will only detect the portion of heritable signal that is consistent across contributing GWAS datasets. A second potential explanation for this discrepancy is that LDSC may produce attenuated heritability estimates because of discrepancies between LD structure in the reference data used to construct the LD scores and the samples from which the GWAS estimates were derived. In addition to these issues, the present findings highlight another, easily correctable, source of discrepancy across LDSC and genomic-relatedness matrix restricted maximum likelihood for binary traits.
