Revisiting the false positive rate in detecting recent positive selection
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- 作者：Jinggong Xiang-Yu ; Zongfeng Yang ; Kun Tang ; Haipeng Li
- 关键词：recent positive selection ; selective sweep ; demography ; population structure ; false positive
- 刊名：Quantitative Biology
- 出版年：2016
- 出版时间：September 2016
- 年：2016
- 卷：4
- 期：3
- 页码：207-216
- 全文大小：318 KB
- 刊物主题：Bioinformatics; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Mathematical and Computational Biology;
- 出版者：Springer Berlin Heidelberg
- ISSN：2095-4697
- 卷排序：4
文摘
There is increasing interest in studying the molecular mechanisms of recent adaptations caused by positive selection in the genomics era. Such endeavors to detect recent positive selection, however, have been severely handicapped by false positives due to the confounding impact of demography and the population structure. To reduce false positives, it is critical to conduct a functional analysis to identify the true candidate genes/mutations from those that are filtered through neutrality tests. However, the extremely high cost of such functional analysis may restrict studies within a small number of model species. In particular, when the false positive rate of neutrality tests is high, the efficiency of the functional analysis will also be very low. Therefore, although the recent improvements have been made in the (joint) inference of demography and selection, our ultimate goal, which is to understand the mechanism of adaptation generally in a wide variety of natural populations, may not be achieved using the currently available approaches. More attention should thus be spent on the development of more reliable tests that could not only free themselves from the confounding impact of demography and the population structure but also have reasonable power to detect selection.