Phylogeny and Genomic Inference for Quantitative Traits

数量性状的系统发育和基因组推断

• 批准号: 7198115
• 负责人: Joseph Felsenstein
• 金额: $ 22.23万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-04-01 至 2009-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7198115
• 关键词: Affect; Biology; Complex; Computer Simulation; Computing Methodologies; Data; Data Analyses; Environment; Event; Evolution; Gene Frequency; Genes; Genetic; Genetic Drift; Genome; Genomics; Individual; Internet; Java; Location; Maps; Markov Chains; Measurable; Measurement; Methods; Modeling; Monte Carlo Method; Motion; Multivariate Analysis; Mutation; Natural Selections; Numbers; Pattern; Phylogenetic Analysis; Phylogeny; Population; Population Biology; Process; Quantitative Genetics; Rate; Sampling; Single Nucleotide Polymorphism; Site; Statistical Methods; Structure; Testing; Variant; Writing; computer program; migration; neglect; programs; trait

DESCRIPTION (provided by applicant): Phylogeny and Genomic Inference for Quantitative Traits It is proposed to develop statistical methods for analyzing data on phenotypic traits within populations, between populations, and between species, in an integrated way. Computer programs will be written and distributed to allow us to compare inferences at these levels and test whether divergence of characters among species shows different patterns of divergence when compared to the same characters observed between populations. Discrete 0/1 traits will be handled as well as quantitatively measurable traits. For the discrete traits, the threshold model of quantitative genetics will be used. Simple models of change of measurable environmental variables will be incorporated as well to allow testing of effects of these environments. These methods will be extended to also be able to handle neutral markers such as SNPs from genomic sequences. The pattern of variation within and between species of these SNPs creates opportunities to test for natural selection, by looking for combinations of characters that have evolved with a noticeably different pattern of covariation than the markers. In this way the testing framework will begin to unify population biology inferences with genomic methods, as genomic methods are increasingly applied to the biology of natural populations.

描述（由申请人提供）：定量性状的系统发育和基因组推断 提议开发统计方法，以分析人群，人群之间和物种之间的表型性状数据，以综合方式。计算机程序将被编写和分发，以使我们能够比较这些级别的推论，并测试与人群之间观察到的相同字符相比，物种之间字符的分歧是否显示出不同的分歧模式。离散的0/1特征将被处理以及定量可测量的特征。对于离散性状，将使用定量遗传学的阈值模型。还将合并可测量环境变量的简单模型，以允许测试这些环境的影响。这些方法将扩展到还能够处理中性标记，例如基因组序列的SNP。这些SNP的种类内部和种类之间的变化模式通过寻找与标记相协方差截然不同的角色的组合，从而创造了测试自然选择的机会。这样，测试框架将开始通过基因组方法统一种群生物学推论，因为基因组方法越来越多地应用于自然种群的生物学。