RAPID MULTIPOINT METHODS FOR MAPPING COMPLEX DISEASES

用于绘制复杂疾病图谱的快速多点方法

• 批准号: 6169588
• 负责人: JEFFREY R O'CONNELL
• 金额: $ 20.98万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-09-30 至 2002-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6169588
• 关键词: analytical method; autosomal recessive trait; biomedical resource; computer data analysis; computer program /software; computer simulation; family genetics; gene environment interaction; gene expression; genetic disorder; genetic susceptibility; genotype; linkage mapping; mathematical model; model design /development; quantitative trait loci

DESCRIPTION (Adapted from the Investigator's Abstract): Parametric linkage models, when carefully applied, can be invaluable in unraveling the complexities of interacting genes in complex diseases. The investigators will develop a faster likelihood engine using novel algorithms to extend the range of possible applications of parametric linkage analysis to include multilocus models to measure interaction between susceptibility genes and regressive models to be able to account for covariates, environmental factors, and familial correlations. Haplotype variation analysis is a very powerful approach to measure the variation of quantitative traits and to aid in their fine mapping. The investigators will develop zero-recombinant haplotype programs to efficiently carry out this analysis. The haplotype program will be particularly useful as array technologies begin to permit rapid genotyping at thousands of single nucleotide polymorphism markers. Simulation is an integral part in many non-parametric approaches and for testing the power of statistical models used in the study of complex diseases. A robust simulation engine based on the faster likelihood engine will be developed by the investigators. The algorithms will be implemented in VITESSE to develop an integrated package for the study of complex diseases using more powerful parametric models. The investigators will rigorously test and validate the computational and simulation engine and haplotyping programs to ensure correctness of the algorithms. They will also optimize the code to run efficiently on all platforms in general use by other researchers. The investigators will document and distribute the programs via the Internet to the worldwide scientific community.

描述（改编自研究者摘要）：参数链接 模型，如果仔细应用，可以在解开 复杂疾病中相互作用基因的复杂性。 调查人员 将开发一个更快的可能性引擎，使用新的算法来扩展 一系列可能的应用参数连锁分析，包括 多位点模型来衡量易感基因之间的相互作用， 回归模型能够解释协变量、环境 因素和家族相关性。 单倍型变异分析是一种非常有效的方法来测量 数量性状的变异，并帮助其精细定位。 的 研究人员将开发零重组单倍型程序， 有效地进行这种分析。 单倍型程序将是 当阵列技术开始允许快速基因分型时 数千个单核苷酸多态性标记。 模拟是许多非参数方法的组成部分， 测试用于复杂研究的统计模型的功效 疾病 基于快速似然引擎的鲁棒仿真引擎 将由研究人员开发。 这些算法将在VITESSE中实现，以开发一个集成的 用于研究复杂疾病的软件包，使用更强大的参数 模型 研究人员将严格测试和验证 计算和模拟引擎和单体型分析程序，以确保 算法的正确性。 他们还将优化代码运行 在其他研究人员普遍使用的所有平台上都有效。 的 调查人员将通过互联网记录和分发这些程序， 全世界的科学界。