The future of data analysis in evolutionary genomics

被引:19
作者
Hughes, Austin L.
Friedman, Robert
Glenn, Nancy L.
机构
[1] Univ S Carolina, Dept Biol Sci, Columbia, SC 29208 USA
[2] Univ S Carolina, Dept Stat, Columbia, SC 29208 USA
关键词
D O I
10.2174/138920206778426942
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Biology as a whole has entered a new era in which data analysis plays a prominent role; but in the field of evolutionary genomics, data analysis has so far yielded little of value. This relative failure has been due in large part to methodological problems. Frequently, researchers have not sufficiently considered alternative hypotheses, leading to a kind of "computer-assisted storytelling". Moreover, there has been widespread use of model-based statistical methods that depend heavily on assumptions regarding evolutionary processes of which we have little knowledge. The field of evolutionary genomics would benefit from a greater use of "sturdy statistics" that are model-free and make few assumptions about processes we do not understand.
引用
收藏
页码:227 / 234
页数:8
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