RT Journal Article
SR Electronic
T1 From Typical Sequences to Typical Genotypes
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 079491
DO 10.1101/079491
A1 Omri Tal
A1 Tat Dat Tran
A1 Jacobus Portegies
YR 2016
UL http://biorxiv.org/content/early/2016/10/06/079491.abstract
AB We demonstrate an application of a core notion of information theory, that of typical sequences and their related properties, to analysis of population genetic data. Based on the asymptotic equipartition property (AEP) for non-stationary discrete-time sources producing independent symbols, we introduce the concepts of typical genotypes and population entropy rate and cross-entropy rate. We analyze three perspectives on typical genotypes: a set perspective on the interplay of typical sets of genotypes from two populations, a geometric perspective on their structure in high dimensional space, and a statistical learning perspective on the prospects of constructing typical-set based classifiers. In particular, we show that such classifiers have a surprising resilience to noise originating from small population samples, and highlight the potential for further links between inference and communication.