Genome wide association analysis (GWAS) has provided numerous insights into the genetic etiology of complex diseases. In this talk, I will first introduce genetic correlation analysis of complex traits, and then introduce LOGODetect, a powerful and efficient statistical method to identify small genome segments harboring local genetic correlation signals. LOGODetect automatically identifies genetic regions showing consistent associations with multiple phenotypes through a scan statistic approach. It uses summary association statistics from genome-wide association studies (GWAS) as input and is robust to sample overlap between studies. Next, I will extend LOGODetect to study cross-ancestry genetic correlation analysis, with application in cross-ancestry polygenic risk prediction.