LIKELIHOOD OF SEQUENCES WITH RECOMBINATION AND SELECTION

重组和选择序列的可能性

• 批准号: 6490081
• 负责人: Joseph Felsenstein
• 金额: $ 19.23万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-01-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6490081
• 关键词: biochemical evolution; computer assisted sequence analysis; computer data analysis; computer program /software; genetic models; genetic recombination; genetic techniques; mathematical model; method development; model design /development; natural selections; nucleic acid sequence; population genetics; statistics /biometry

This proposal will continue the development of methods for making likelihood inferences from population samples of molecular sequences, where there may be recombination within the sequences and natural selection affecting some sites. Molecular and population biologists have continued to collect increasing amounts of such data; as in other areas, likelihood methods will become important in their analysis. Population biologists want to use the sequences to understand population history and evolutionary forces, while molecular biologists will want to use within-species variation to understand which regions of a molecule are constrained from varying. It is proposed to develop statistical methods for approximately computing the likelihoods of population parameters, such as effective population sizes and population growth rates; genetic parameters such as the rate of recombination; and patterns of natural selection such as balancing selection or directional selection acting at particular sites. The likelihoods can be computed if we can sum them over all the possible recombining genealogies connecting the members of an observed sample. While there are far too many genealogies to do the sum exactly, Markov Chain Monte Carlo methods such as the Metropolis-Hastings method can be used to draw a large enough random sample of genealogies, and use these to estimate the likelihood curves. Previous work has developed algorithms for recombining sequences; the present proposal will new methods for calculating the likelihoods in the presence of natural selection at specific sites. It will also integrate the existing methods into a usable whole which will allow biologists to construct an analysis of the particular combination of evolutionary forces that they want to consider. The methods are computer intensive; they will be made available, free, over the Internet, as the LAMARC package of programs distributed in C source code and as executables.

该建议将继续开发制造方法 分子种群样本的可能性推断 序列，序列内可能存在重组 和自然选择会影响某些站点。 分子和 人口生物学家继续收集越来越多的 此类数据的数量；与其他领域一样，可能的方法将 在分析中变得重要。 人口生物学家想要 使用序列来了解人口历史和 进化力，而分子生物学家将要使用 种类内变化以了解一个区域 分子受到不同的约束。 建议开发统计方法以大致 计算人口参数的可能性，例如 有效的人口规模和人口增长率；遗传 参数，例如重组率；和模式 自然选择，例如平衡选择或定向 选择在特定站点上表演。 可能性可能是 如果我们可以在所有可能的重组中总结它们，则计算 连接观察到的样品成员的家谱。 尽管 马尔可夫有太多的家谱要准确地完成总和 连锁蒙特卡洛方法，例如大都会危机方法 可用于绘制足够大的随机样本样本， 并使用这些来估计可能性曲线。 以前的工作 已经开发了用于重组序列的算法；现在 提案将新的方法用于计算中的可能性 在特定地点存在自然选择。 它也会 将现有方法集成到可用的整体中 允许生物学家对特定的分析进行分析 他们要考虑的进化力的结合。 这些方法是计算机密集型的；他们将被提供， 免费，通过互联网作为lamarc程序包 在C源代码和可执行文件中分发。