Developing Statistics Methods to Detect Rare Genetics Variants in Human Complex Pedigrees

我们提出了一种基于系谱的稀有变异分析方法，将每个受影响的亲属视为依赖对，并使用相关矩阵来解释这种依赖关系。这项工作促成了两本书的出版。我们现在正致力于使用一种基于单倍型的方法来识别人类疾病的因果变异，如精神分裂症、双相情感障碍和强迫症。我们已经从DBGaP获得了相关数据集，这将使我们能够比较各种分析方法所给出的统计特性。 我们为约翰·霍普金斯大学医学院杰拉尔德·内斯塔特教授领导的强迫症研究做出了贡献。

We have developed pedigree-based rare variants analysis approach by treating each affected relative as dependent pairs and the dependency will be accounted for using correlation matrix. This work led to two publications. We are now working on using a haplotype-based approach to identify causal variants for human diseases such as schizophrenia, bipolar, and obsessive compulsive disorder. We have obtained the relevant data sets from dbGap which will allow us to compare the statistical properties given by various types of analytical methods. We have made contributions to a study of obsessive compulsive disorder, led by Professor Gerald Nestadt at the Medical School of Johns Hopkins University.