zhengcq / hdl

High-definition likelihood inference of genetic correlations (HDL)

What is HDL?

High-Definition Likelihood (HDL) is a likelihood-based method for estimating genetic correlation using GWAS summary statistics. Compared to LD Score regression (LDSC), It reduces the variance of a genetic correlation estimate by about 60%. Here, we provide an R-based computational tool HDL to implement our method. Although HDL is written in R, you can use it with the command line. So no worry if you are not an R user.

In the wiki, we provide a detailed tutorial for the application of HDL together with real examples.

What data are required?

• gwas1.df and gwas2.df, which are two datasets including GWAS summary statistics of genetic variants for two traits. This page describes the format of summary statistics for HDL, and how to perform data wrangling.

• The eigenvalues and eigenvectors of LD matrices. For the European-ancestry population, we have computed the LD matrices and their eigen-decomposition from 336,000 Genomic British individuals in UK Biobank. You can download these pre-computed reference files following the instruction in the wiki.

For Help

For direct R documentation of HDL.rg function, you can use a question mark in R:

?HDL.rg

If you have specific questions, you may email the maintainer of HDL via [email protected].