Department of Electrical & Computer Engineering, University of California San Diego, La Jolla, California, USA.
Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA.
Nat Methods. 2018 Apr;15(4):279-282. doi: 10.1038/nmeth.4606. Epub 2018 Feb 19.
Most approaches that capture signatures of selective sweeps in population genomics data do not identify the specific mutation favored by selection. We present iSAFE (for "integrated selection of allele favored by evolution"), a method that enables researchers to accurately pinpoint the favored mutation in a large region (∼5 Mbp) by using a statistic derived solely from population genetics signals. iSAFE does not require knowledge of demography, the phenotype under selection, or functional annotations of mutations.
大多数在群体基因组学数据中捕获选择信号的方法并不能确定被选择所青睐的具体突变。我们提出了 iSAFE（代表“进化选择的等位基因的综合选择”），这是一种方法，它可以让研究人员仅通过群体遗传学信号得出的统计数据，准确地确定一个大区域（约 5 Mbp）内被选择所青睐的突变。iSAFE 不需要了解人口统计学、选择下的表型或突变的功能注释。
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