Journal ArticleDOI
Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment.
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TLDR
This paper showed that the likelihood equations used by versions 1.0 and 2.0 of CERVUS to accommodate genotyping error miscalculate the probability of observing an erroneous genotype.Abstract:
Genotypes are frequently used to identify parentage. Such analysis is notoriously vulnerable to genotyping error, and there is ongoing debate regarding how to solve this problem. Many scientists have used the computer program CERVUS to estimate parentage, and have taken advantage of its option to allow for genotyping error. In this study, we show that the likelihood equations used by versions 1.0 and 2.0 of CERVUS to accommodate genotyping error miscalculate the probability of observing an erroneous genotype. Computer simulation and reanalysis of paternity in Rum red deer show that correcting this error increases success in paternity assignment, and that there is a clear benefit to accommodating genotyping errors when errors are present. A new version of CERVUS (3.0) implementing the corrected likelihood equations is available at http://www.fieldgenetics.com.read more
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References
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Journal ArticleDOI
Statistical confidence for likelihood-based paternity inference in natural populations
TL;DR: This study derives likelihood ratios for paternity inference with codominant markers taking account of typing error, and defines a statistic Δ for resolving paternity, and demonstrates the method is robust to their presence under commonly encountered conditions.
Journal ArticleDOI
How to track and assess genotyping errors in population genetics studies.
Aurélie Bonin,Eva Bellemain,P. Bronken Eidesen,François Pompanon,Christian Brochmann,Pierre Taberlet +5 more
TL;DR: Four case studies representing a large variety of population genetics investigations differing in their sampling strategies, in the type of organism studied (plant or animal) and the molecular markers used [microsatellites or amplified fragment length polymorphisms (AFLPs), and the estimated genotyping error rate are considered.
Journal ArticleDOI
Genotyping errors: causes, consequences and solutions.
TL;DR: A protocol for estimating error rates is proposed and it is recommended that these measures be systemically reported to attest the reliability of published genotyping studies.
Journal ArticleDOI
Sibship reconstruction from genetic data with typing errors.
TL;DR: Simulations show that a new likelihood method with simple and robust models of typing error incorporated into it can be used to infer full- and half-sibships accurately from marker data with a high error rate and to identify typing errors at each locus in each reconstructed sib family.
Journal ArticleDOI
ml‐relate: a computer program for maximum likelihood estimation of relatedness and relationship
TL;DR: A computer program, ml - relate, that calculates maximum likelihood estimates of relatedness and relationship and uses simulation to determine which relationships are consistent with genotype data and to compare putative relationships with alternatives.
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