RAPID MULTIPOINT METHODS FOR MAPPING COMPLEX DISEASES

用于绘制复杂疾病图谱的快速多点方法

基本信息

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
项目类别：
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

项目摘要

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（改编自研究者的摘要）：参数链接如果仔细应用这些模型，对于揭示问题的本质是无价的。复杂疾病中相互作用基因的复杂性。调查人员将使用新颖的算法开发更快的似然引擎来扩展参数联动分析的可能应用范围包括多位点模型来测量易感基因和回归模型能够解释协变量、环境因素和家庭相关性。单倍型变异分析是一种非常强大的方法来测量数量性状的变化并有助于其精细绘图。这研究人员将开发零重组单倍型计划有效地进行此分析。单倍型程序将是当阵列技术开始允许快速基因分型时特别有用数千个单核苷酸多态性标记。仿真是许多非参数方法中不可或缺的一部分，对于测试复杂研究中使用的统计模型的威力疾病。基于更快似然引擎的强大模拟引擎将由研究人员开发。这些算法将在 VITESSE 中实施，以开发集成的使用更强大的参数来研究复杂疾病的包模型。调查人员将严格测试和验证计算和模拟引擎以及单倍型程序，以确保算法的正确性。他们还将优化运行代码在其他研究人员普遍使用的所有平台上高效地工作。这调查人员将记录这些程序并通过互联网分发给全世界科学界。