On minimizing assignment errors and the trade-off between false positives and negatives in parentage analysis

Area of Science:

• Ecology
• Genetics
• Wildlife Biology

Background:

• Genetic parentage analysis is crucial for identifying parent-offspring relationships in wild populations.
• Previous research highlighted the importance of microsatellite loci number and diversity for accurate assignments.
• Certain parentage analysis methods, like exclusion-Bayes theorem, showed higher susceptibility to errors.

Purpose of the Study:

• To analyze and discuss the trade-off between Type I (false-positive) and Type II (false-negative) errors in genetic parentage analyses.
• To emphasize the potential for misleading results when only controlling for false-positive assignments.

Main Methods:

• Comparative analysis of three parentage analysis methods.
• Simulation studies to assess assignment accuracy.
• Evaluation of Type I and Type II error rates.

Main Results:

• The number and diversity of microsatellite loci significantly influence parentage assignment accuracy.
• Exclusion-Bayes theorem methods were found to be more prone to both false-positive and false-negative assignments.
• Controlling solely for false-positive assignments without considering false-negative rates can be misleading.

Conclusions:

• Accurate genetic parentage analysis necessitates the estimation and reporting of both false-positive and false-negative error rates.
• A comprehensive understanding of both error types is essential for reliable parent-offspring relationship determination in wildlife.
• Future parentage analyses should prioritize reporting both Type I and Type II error rates for transparency and validity.