Computational Haplotype Analysis for SNPs

描述(申请人提供)：对于复杂的性状，以系谱为基础 连锁分析可有效地将疾病相关基因定位到 1厘米。这一区域内疾病突变的精细图谱通常是可以实现的。 利用单倍型进行连锁不平衡分析。单倍型也可以是 非常有助于对患者进行分层，并将药物引导到适当的 亚群。人类单核苷酸多态(SNP)AS的发现 遗传标记的出现极大地增加了遗传图谱的密度，增强了 我们开发新的疾病诊断工具和个性化的能力 药物疗法。然而，165万个人类SNPs单核苷酸 多态(SNP)标记鉴定、单倍型测定和分析 向科学家提出了一个令人生畏的挑战。这项研究的总体目标是 是为了提高我们的计算能力，既可以构建 群体单倍型及全单倍型信息的利用 LD映射。拟议研究的具体目标是：(A)提出更多 用于单倍型确定的高效且可扩展的计算策略， (B)证明在电子计算机中确定单倍型的方法是 有效和经济的替代试验方案；(C)建立一种 允许直接输出单倍型的计算平台 高通量基因分型读数，以及(D)设计贝叶斯框架 同时进行单倍型测定、LD作图和患者聚类。

DESCRIPTION (provided by applicant): For a complex trait, the pedigree-based llinkage analysis is effective for localizing disease-related genes to within 1cM. Fine-mapping of the disease mutation within this region is often achieved by linkage disequilibrium analysis using haplotypes. Haplotypes can also be very useful for stratifying patients and directing drugs to appropriate subpopulation. The discovery of human single nucleotides polymorphism (SNP) as genetic marker's greatly increases the density of the genetic map and enhances our ability in developing novel disease diagnostic tools and individualized drug therapies. However, with 1.65 million human SNPs single nucleotides polymorphism (SNP) markers identified, the haplotype determination and analysis present a daunting challenge to scientists. The general goal of this research is to advance our computational capability for both the construction of population haplotypes and the utilization of the whole haplotype information in LD mapping. The specific aims of the proposed research are (a) to propose more efficient and scalable computational strategies for haplotype determination, (b) to demonstrate that in silico approaches to haplotype determinations are effective and economical alternatives to experimental ones, (c) to establish a computational platform that allows for a direct output of haplotypes from high-throughput genotyping readouts, and (d) to design a Bayesian framework for simultaneous haplotype determination, LD mapping, and patients clustering.