In statistical genetics, linkage disequilibrium score regression (LDSR[1] or LDSC[2]) is a technique that aims to quantify the separate contributions of polygenic effects and various confounding factors, such as population stratification, based on summary statistics from genome-wide association studies (GWASs).
The approach involves using regression analysis to examine the relationship between linkage disequilibrium scores and the test statistics of the single-nucleotide polymorphisms (SNPs) from the GWAS.
Because the LDSC approach relies only on summary statistics from an entire GWAS, it can be used efficiently even with very large sample sizes.
[4] In LDSC, genetic correlations are calculated based on the deviation between chi-square statistics and what would be expected assuming the null hypothesis.
[5][6] Another extension of LDSC, known as stratified LD score regression (abbreviated SLDSR),[7] aims to partition heritability by functional annotation by taking into account genetic linkage between markers.