Nielsen R
Department of Biometrics, Cornell University, 439 Warren Hall, Ithaca, NY 14853-7801, USA.
Heredity (Edinb). 2001 Jun;86(Pt 6):641-7. doi: 10.1046/j.1365-2540.2001.00895.x.
Examining genomic data for traces of selection provides a powerful tool for identifying genomic regions of functional importance. Many methods for identifying such regions have focused on conserved sites. However, positive selection may also be an indication of functional importance. This article provides a brief review of some of the statistical methods used to detect selection using DNA sequence data or other molecular data. Statistical tests based on allelic distributions or levels of variability often depend on strong assumptions regarding population demographics. In contrast, tests based on comparisons of the level of variability in nonsynonymous and synonymous sites can be constructed without demographic assumptions. Such tests appear to be useful for identifying specific regions or specific sites targeted by selection.
检查基因组数据中的选择痕迹为识别具有功能重要性的基因组区域提供了一个强大的工具。许多识别此类区域的方法都集中在保守位点上。然而，正选择也可能表明功能上的重要性。本文简要回顾了一些利用DNA序列数据或其他分子数据来检测选择的统计方法。基于等位基因分布或变异水平的统计检验通常依赖于关于种群统计学的强假设。相比之下，基于非同义位点和同义位点变异水平比较的检验可以在不做种群统计学假设的情况下构建。此类检验似乎有助于识别受选择作用的特定区域或特定位点。
