STORM: software for testing hypotheses of relatedness and mating patterns.

Area of Science:

• Population genetics
• Behavioral ecology
• Computational biology

Background:

• Understanding population structure and mating behaviors is crucial in evolutionary biology.
• Quantifying genetic relatedness and compatibility informs studies on social behavior and reproductive success.

Purpose of the Study:

• To introduce Storm, a software package for testing hypotheses related to population relatedness and mate choice.
• To provide tools for calculating internal relatedness, homozygosity by loci, pairwise relatedness, and a novel allele inheritance metric.

Main Methods:

• The Storm software package utilizes four core calculations: internal relatedness, homozygosity by loci, pairwise relatedness, and allele inheritance.
• It integrates these calculations within a hypothesis-testing framework, employing Monte Carlo simulations.
• Hypotheses tested include relatedness in groupings, offspring genetic variability, mating pair relatedness, and Mendelian inheritance patterns.

Main Results:

• Storm enables independent calculation of relatedness and inheritance metrics.
• The software facilitates hypothesis testing on population structure, mate choice, and genetic variability.
• Monte Carlo simulations are used to compare observed patterns against expected values.

Conclusions:

• Storm provides a robust computational framework for investigating genetic relatedness and mating patterns in populations.
• The software's metrics and hypothesis-testing capabilities offer valuable insights into evolutionary processes.
• It serves as a tool for researchers in population genetics and behavioral ecology.