论文标题
从基因组数据中推断遗传适应性
Inferring genetic fitness from genomic data
论文作者
论文摘要
自然发展群体的遗传组成被认为是由于突变，选择，遗传漂移和重组。选择被建模为单位级别术语（加性适应性）和两局部项（成对的上皮适应性）。这个问题是为了从不断发展的人群的时间序列中从人口范围的全基因组数据中推断出同志适应性。我们在计算机中生成了此类数据，并表明在Kimura，Neher和Shraiman的准链接平衡（QLE）相中，以高足够的重组率和低的突变速率呈现，可以使用逆Ising/Potts方法定量地推断出敏感性适应性。
The genetic composition of a naturally developing population is considered as due to mutation, selection, genetic drift and recombination. Selection is modeled as single-locus terms (additive fitness) and two-loci terms (pairwise epistatic fitness). The problem is posed to infer epistatic fitness from population-wide whole-genome data from a time series of a developing population. We generate such data in silico, and show that in the Quasi-Linkage Equilibrium (QLE) phase of Kimura, Neher and Shraiman, that pertains at high enough recombination rates and low enough mutation rates, epistatic fitness can be quantitatively correctly inferred using inverse Ising/Potts methods.
