Crona Kristina
American University, Washington, D.C., United States of America.
PLoS Genet. 2016 Dec 22;12(12):e1006322. doi: 10.1371/journal.pgen.1006322. eCollection 2016 Dec.
Epistasis is a key concept in the theory of adaptation. Indicators of epistasis are of interest for large systems where systematic fitness measurements may not be possible. Some recent approaches depend on information theory. We show that considering shared entropy for pairs of loci can be misleading. The reason is that shared entropy does not imply epistasis for the pair. This observation holds true also in the absence of higher order epistasis. We discuss a method for reducing the number of false positives. However, our main conclusion is that entropy-based approaches have serious limitations in this context.
上位性是适应理论中的一个关键概念。对于无法进行系统适合度测量的大型系统而言,上位性指标备受关注。一些近期的方法依赖于信息论。我们表明,考虑基因座对的共享熵可能会产生误导。原因在于共享熵并不意味着该基因座对存在上位性。这一观察结果在不存在高阶上位性的情况下同样成立。我们讨论了一种减少假阳性数量的方法。然而,我们的主要结论是,基于熵的方法在这种情况下存在严重局限性。