genhet: an easy-to-use R function to estimate individual heterozygosity

Area of Science:

• Population Genetics
• Bioinformatics
• Computational Biology

Background:

• Estimating individual heterozygosity is crucial in population genetics for studies on inbreeding, genetic diversity, and evolutionary potential.
• Existing computational tools may have limitations regarding dataset size or type, hindering broad applicability.

Purpose of the Study:

• To introduce genhet, a novel R function designed for calculating multiple estimates of individual heterozygosity.
• To provide a flexible and user-friendly tool applicable to diverse diploid genotype datasets.

Main Methods:

• Development of the genhet function in R programming language.
• Implementation of five commonly used heterozygosity estimation algorithms.
• Testing the function's performance across various simulated and empirical diploid genotype datasets of varying sizes.

Main Results:

• The genhet function successfully calculates five standard heterozygosity estimates.
• Demonstrated applicability to diploid genotype data irrespective of the number of individuals, loci, or alleles.
• The accompanying manual facilitates straightforward use, even for novice R users.

Conclusions:

• genhet offers a robust and adaptable solution for quantifying individual heterozygosity in population genetic studies.
• The function's ease of use and broad applicability make it a valuable resource for researchers in genetics and evolutionary biology.