Allelematch: an R package for identifying unique multilocus genotypes where genotyping error and missing data may be...

Area of Science:

• Molecular Ecology
• Population Genetics
• Bioinformatics

Background:

• Noninvasive sampling protocols often yield data with unknown individual numbers, genotyping errors, and missing data.
• Accurate identification of unique multilocus genotypes is crucial for population studies.

Purpose of the Study:

• To introduce allelematch, an R package designed to automate the identification of unique multilocus genotypes.
• To provide a tool for handling complex population genetic datasets common in noninvasive sampling.

Main Methods:

• Development of the allelematch R package for genotype identification.
• Utilizing simulations to assess the performance and accuracy of the allelematch package.
• Evaluating performance across various data set properties, including genotyping error rates.

Main Results:

• Allelematch reliably and accurately determines the correct number of unique genotypes (± 3%) across diverse data set properties.
• The software achieves highest accuracy when genotyping error rates are below 4%.

Conclusions:

• Allelematch offers a valuable solution for processing large sample sizes and identifying unique genotypes in molecular ecology.
• The package facilitates comparisons of genotypes and review of profile differences, supporting spatial and temporal population monitoring.