4.7 Article

Sequencing era methods for identifying signatures of selection in the genome

期刊

BRIEFINGS IN BIOINFORMATICS
卷 20, 期 6, 页码 1997-2008

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bby064

关键词

natural selection; machine learning; selective sweep; genome sequencing; recombination

资金

  1. University of Southampton Institute for Life Sciences
  2. Faculty of Medicine
  3. Department of Mathematics

向作者/读者索取更多资源

Insights into genetic loci which are under selection and their functional roles contribute to increased understanding of the patterns of phenotypic variation we observe today. The availability of whole-genome sequence data, for humans and other species, provides opportunities to investigate adaptation and evolution at unprecedented resolution. Many analytical methods have been developed to interrogate these large data sets and characterize signatures of selection in the genome. We review here recently developed methods and consider the impact of increased computing power and data availability on the detection of selection signatures. Consideration of demography, recombination and other confounding factors is important, and use of a range of methods in combination is a powerful route to resolving different forms of selection in genome sequence data. Overall, a substantial improvement in methods for application to whole-genome sequencing is evident, although further work is required to develop robust and computationally efficient approaches which may increase reproducibility across studies.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据