Publications by authors named "Lu-Cheng Pi"
Article Synopsis
- The study analyzes the statistical performance of various burden tests (like CMC, WST, SUM) in genetic association studies focused on rare variants using simulated datasets.
- Results indicate that the type I error rate for all tests is close to 0.05, and the power of these methods varies based on factors like linkage disequilibrium (LD) and the effect direction of the variants.
- It concludes that factors such as sample size, effect direction, and the presence of non-associated variants significantly influence the effectiveness of these burden tests, highlighting the importance of integrating prior biological information when selecting methods.
