PT  - JOURNAL ARTICLE
AU  - Brielin C. Brown
AU  - Asian Genetic Epidemiology Network-Type 2 Diabetes (AGEN-T2G) Consortium
AU  - Chun Jimmie Ye
AU  - Alkes L. Price
AU  - Noah Zaitlen
TI  - Transethnic genetic correlation estimates from summary statistics
AID  - 10.1101/036657
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 036657
4099  - http://biorxiv.org/content/early/2016/02/23/036657.short
4100  - http://biorxiv.org/content/early/2016/02/23/036657.full
AB  - The increasing number of genetic association studies conducted in multiple populations provides unprecedented opportunity to study how the genetic architecture of complex phenotypes varies between populations, a problem important for both medical and population genetics. Here we develop a method for estimating the transethnic genetic correlation: the correlation of causal variant effect sizes at SNPs common in populations. We take advantage of the entire spectrum of SNP associations and use only summary-level GWAS data. This avoids the computational costs and privacy concerns associated with genotype-level information while remaining scalable to hundreds of thousands of individuals and millions of SNPs. We apply our method to gene expression, rheumatoid arthritis, and type-two diabetes data and overwhelmingly find that the genetic correlation is significantly less than 1. Our method is implemented in a python package called popcorn.