arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1607.04372q-bio.PE
收藏

基于站点频率数据的速率矩阵估计

Rate Matrix Estimation From Site Frequency Data

Conrad J. Burden, Yurong Tang

摘要:

描述了一个从观测站点频率数据估计进化速率矩阵的过程。该过程假设(1)数据是从根据固定Wright-Fisher模型进化的恒定大小的群体获得的;(2)数据由从群体中随机抽取的中等数量的测序基因组的多重比对组成;以及(3)在基因组内,可以鉴定出大量独立的、中性的位点,这些位点以共同的突变率矩阵进化。除了非对角元素为正且<<1以及行总和为零之外,对缩放速率矩阵没有施加限制。特别地,速率矩阵不被假设为可逆的。该方法的关键是在低突变率极限下求多等位基因中立Wright-Fisher模型正向Kolmogorov方程的近似平稳解。

英文摘要:

A procedure is described for estimating evolutionary rate matrices from observed site frequency data. The procedure assumes (1) that the data are obtained from a constant size population evolving according to a stationary Wright-Fisher model; (2) that the data consist of a multiple alignment of a moderate number of sequenced genomes drawn randomly from the population; and (3) that within the genome a large number of independent, neutral sites evolving with with a common mutation rate matrix can be identified. No restrictions are imposed on the scaled rate matrix other than that the off-diagonal elements are positive and <<1, and that the rows sum to zero. In particular the rate matrix is not assumed to be reversible. The key to the method is an approximate stationary solution to the forward Kolmogorov equation for the multi-allele neutral Wright-Fisher model in the limit of low mutation rates.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑