An efficient family-based association test using multiple markers

✍ Scribed by Xin Xu; Cyril Rakovski; Xiping Xu; Nan Laird

• Publisher: John Wiley and Sons
• Year: 2006
• Tongue: English
• Weight: 153 KB
• Volume: 30
• Category: Article
• ISSN: 0741-0395
• DOI: 10.1002/gepi.20174

✦ Synopsis

In genetic association studies, multiple markers are usually employed to cover a genomic region of interest for localizing a trait locus. In this report, we propose a novel multi-marker family-based association test (T LC ) that linearly combines the single-marker test statistics using data-driven weights. We examine the type-I error rate in a numerical study and compare its power to identify a common trait locus using tag single nucleotide polymorphisms (SNPs) within the same haplotype block that the trait locus resides with three competing tests including a global haplotype test (T H ), a multi-marker test similar to the Hotelling-T 2 test for the population-based data (T MM ), and a single-marker test with Bonferroni's correction for multiple testing (T B ). The type-I error rate of T LC is well maintained in our numeric study. In all the scenarios we examined, T LC is the most powerful, followed by T B . T MM and T H are the poorest. T H and T MM have essentially the same power when parents are available. However, when both parents are missing, T MM is substantially more powerful than T H . We also apply this new test on a data set from a previous association study on nicotine dependence.