Abo Ryan, Knight Stacey, Wong Jathine, Cox Angela, Camp Nicola J
Department of Biomedical Informatics, University of Utah, UT, USA.
Bioinformatics. 2008 Sep 15;24(18):2105-7. doi: 10.1093/bioinformatics/btn359. Epub 2008 Jul 23.
Haplotypes carry important information that can direct investigators towards underlying susceptibility variants, and hence multiple tagging single nucleotide polymorphisms (tSNPs) are usually studied in candidate gene association studies. However, it is often unknown which SNPs should be included in haplotype analyses, or which tests should be performed for maximum power. We have developed a program, hapConstructor, which automatically builds multi-locus SNP sets to test for association in a case-control framework. The multi-SNP sets considered need not be contiguous; they are built based on significance. An important feature is that the missing data imputation is carried out based on the full data, for maximal information and consistency. HapConstructor is implemented in a Monte Carlo framework and naturally extends to allow for significance testing and false discovery rates that account for the construction process and to related individuals. HapConstructor is a useful tool for exploring multi-locus associations in candidate genes and regions.
单倍型携带重要信息，可引导研究人员找到潜在的易感变异，因此在候选基因关联研究中通常会研究多个标签单核苷酸多态性（tSNP）。然而，通常不清楚单倍型分析应包含哪些单核苷酸多态性（SNP），或者应进行哪些检验以获得最大效能。我们开发了一个程序hapConstructor，它能自动构建多位点SNP集，以便在病例对照框架中进行关联检验。所考虑的多SNP集不必是连续的；它们是基于显著性构建的。一个重要特征是，缺失数据插补是基于完整数据进行的，以获得最大信息和一致性。HapConstructor是在蒙特卡罗框架中实现的，自然扩展后可进行考虑构建过程和相关个体的显著性检验及错误发现率计算。HapConstructor是探索候选基因和区域中多位点关联的有用工具。
