AI Article Synopsis
- The study introduces a new method for measuring how much information polymorphic genetic markers provide about ancestry using an axiomatic approach.
- It uncovers surprising characteristics of a decision-theoretic measure that aligns with the proposed criteria for multilocus informativeness, particularly emphasizing the relationship between population prior information and genetic variant data.
- The research highlights limitations of mutual information-based measures when considering population priors and assesses the reduction in informativeness that occurs when learning from limited population samples.
Article Abstract
We present an axiomatic approach for multilocus informativeness measures for determining the amount of information that a set of polymorphic genetic markers provides about individual ancestry. We then reveal several surprising properties of a decision-theoretic based measure that is consistent with the set of proposed criteria for multilocus informativeness. In particular, these properties highlight the interplay between information originating from population priors and the information extractable from the population genetic variants. This analysis then reveals a certain deficiency of mutual information based multilocus informativeness measures when such population priors are incorporated. Finally, we analyse and quantify the inevitable inherent decrease in informativeness due to learning from finite population samples.
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| http://dx.doi.org/10.1016/j.mbs.2018.10.011 | DOI Listing |
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