InfoMating: Non-random mating and Information Theory



If you use Infomating please cite:

Carvajal-Rodríguez, A. 2019. Multi-model inference of non-random mating from an information theoretic approach.


  1. Carvajal-Rodríguez, A., 2018. Non-random mating and information theory. Theoretical Population Biology 120, 103-113.


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The study of non-random mating, its causes and consequences, is an active area of evolutionary research. From an evolutionary perspective, mate choice has importance by its consequences, as long as it implies a systematic change in phenotype and genotype frequencies. The consequences of non-random mating can be partitioned into sexual selection and assortative mating (sexual isolation or intersexual selection) patterns.

Sexual selection refers to the observed change in gene or phenotype frequencies in mated individuals with respect to population frequencies. Because the population frequencies are involved, the comparison include non-mated individuals.

Assortative mating considers the deviation from random mating within mated individuals. Because we only use frequencies within the mating sample, the comparison do not involve non-mated individuals.

The causes of both type of effects can be a different preference between different mating types, i.e. mate choice (e.g. females A prefer males A) and/or intrasexual competition or differential vigour, of a type from one sex for mating whatever the couple (v.g. males of some type C systematically invests more energy on mating).

We can consider jointly both concepts by means of the so called mutual mating propensity parameters mij that model the mating propensity for each kind of couple (i,j). Therefore, mate choice can be modeled as the mating propensity of females A with males A being higher than with males B or C, on the other side, intrasexual competition can be modeled as a higher marginal propensity of males C for mating any female type (Carvajal-Rodriguez bioRxiv 2019).

Relying on the informational partition of the non-random mating effects, and by modeling mate choice and competition by the mutual propensity parameters, it is possible to identify the necessary and sufficient conditions of random mating and from here, develop and connect different kinds of models producing different effects. These models can be used to generate inferences on the parameters of interest. The software InfoMating implements the methodology to do so.


A. Carvajal-Rodriguez - Departamento de Bioquímica Genética e Inmunología - Universidad de Vigo. ( Last update: February 2019)