Assumptions about frequency-dependent architectures of complex traits bias measures of functional enrichment

Authors: Shadi Zabad, Aaron P. Ragsdale, Rosie Sun, Yue Li, Simon Gravel

This repository contains code to compute LD Scores using the D^2 statistic and carry out the analyses discussed in the manuscript.

Abstract: Linkage-Disequilibrium Score Regression (LDSC) is a popular framework for analyzing GWAS summary statistics that allows for estimating SNP heritability, confounding, and functional enrichment of genetic variants with different annotations. Recent work has highlighted the influence of implicit and explicit assumptions of the model on the biological interpretation of the results. In this work, we explored a formulation of LDSC that replaces the $r^2$ measure of LD with a recently-proposed unbiased estimator of the $D^2$ statistic. In addition to modest statistical difference across estimators, this derivation highlighted implicit and unrealistic assumptions about the relationship between allele frequency, effect size, and annotation status. We carry out a systematic comparison of alternative LDSC formulations by applying them to summary statistics from 47 GWAS traits. Our results show that commonly used models likely underestimate functional enrichment. These results highlight the importance of calibrating the LDSC model to achieve a more robust understanding of polygenic traits.