Biological vs. Statistical Epistasis
There is a new paper in PLoS Genetics by Clayton that highlights the challenges of making biological inferences from statistical models of interaction. I was surprised to see our 2006 paper in the Journal of Theoretical Biology cited as an example of confusing mathematical and biological interaction. Clayton interpreted our paper as saying that we can make causal statements from statistical models. Quite to the contrary, we highlight in our paper the enormous challenges faced when trying to make inferences about the biology happening at the cellular level from a statistical model summarizing population-level data. He also misinterpreted our use of information theory in this paper. We very clearly state in this paper and many others that entropy measures are useful for "statistical" interpretation. We never say anywhere that this is any type of biological interpretation. Clayton should have read and cited our 2005 BioEssays paper that goes through the difference between biological and statistical epistasis in great detail.
I see the Clayton paper as a defense of the status quo statistical approach to genetic association studies. I think he missed an important opportunity here to recognize, as Snyder did in 1951 (see previous post), the value of looking at genetic association data from multiple different points of view using multiple different statistical and computational methods. After all, there is no free lunch.
Clayton DG. Prediction and interaction in complex disease genetics: experience in type 1 diabetes. PLoS Genet. 2009 Jul;5(7):e1000540. [PubMed]
Moore JH, Gilbert JC, Tsai CT, Chiang FT, Holden T, Barney N, White BC. A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility. J Theor Biol. 2006 Jul 21;241(2):252-61. [PubMed]
Moore JH, Williams SM. Traversing the conceptual divide between biological and statistical epistasis: systems biology and a more modern synthesis. Bioessays. 2005 Jun;27(6):637-46. [PubMed]