Sib-parentage testing using molecular markers when parents are unknown.

Area of Science:

• Genetics
• Bioinformatics
• Statistical analysis

Background:

• Determining sibling relationships is crucial in genetics and animal breeding.
• Existing methods for parentage assignment require robust statistical frameworks.

Purpose of the Study:

• To present formulae for calculating the Sib Index for full-sib and half-sib parentage.
• To establish hypothesis testing methods using likelihood ratios and Bayes' factors.
• To evaluate the number of marker systems needed for accurate sib parentage assignment.

Main Methods:

• Development of formulae for the Sib Index using codominant alleles.
• Hypothesis testing based on conditional likelihood ratio and Bayes' factor distributions.
• Simulations to determine thresholds, P-values, and power based on allele number and frequency.

Main Results:

• Formulae for Sib Index computation are provided for both full-sib and half-sib scenarios.
• Simulations demonstrate that approximately 20 marker systems provide adequate power for accepting sib parentage hypotheses.
• A higher number of markers is required for distinguishing between full-sib and half-sib relationships.

Conclusions:

• The Sib Index, with appropriate statistical testing, is a reliable tool for parentage assignment.
• The number of marker systems significantly impacts the power to detect sib relationships.
• Sampling variation in allele frequencies can affect the power of these analyses.