The article by Jinliang Wang addresses the issue of reconstructing sibships from genetic data, particularly in the presence of typing errors. Traditional likelihood methods assume that genetic marker data are error-free, which is rarely the case in practice. Wang proposes a new likelihood method that incorporates simple and robust models of typing errors, which can significantly bias sibship estimates if not accounted for. The method is tested through simulations and applied to empirical data sets. Key contributions include: 1. **New Likelihood Method**: A new likelihood method is introduced that incorporates two types of typing errors (allotypic dropouts and other stochastic errors) into the sibship reconstruction process. This method is shown to accurately infer full- and half-sibships even with high error rates. 2. **Iterative Procedure**: The method uses an iterative procedure to update allele frequencies, improving the accuracy of relationship inference. 3. **Parental Genotype Inference**: The method also allows for the inference of parental genotypes, which can be crucial for understanding the mating system and social behavior of species. 4. **Error Detection**: The method can identify typing errors at each locus within each reconstructed sib family, enhancing the reliability of the results. 5. **Empirical Application**: The proposed methods are applied to two empirical data sets to infer sibship structures and mating systems, demonstrating their practical utility. The article emphasizes the importance of accounting for typing errors in sibship reconstruction, as ignoring them can lead to severe biases in relationship inference. The simulations show that the new method can handle high error rates and provide accurate estimates, making it a valuable tool for researchers in behavioral, ecological, and evolutionary genetics.The article by Jinliang Wang addresses the issue of reconstructing sibships from genetic data, particularly in the presence of typing errors. Traditional likelihood methods assume that genetic marker data are error-free, which is rarely the case in practice. Wang proposes a new likelihood method that incorporates simple and robust models of typing errors, which can significantly bias sibship estimates if not accounted for. The method is tested through simulations and applied to empirical data sets. Key contributions include: 1. **New Likelihood Method**: A new likelihood method is introduced that incorporates two types of typing errors (allotypic dropouts and other stochastic errors) into the sibship reconstruction process. This method is shown to accurately infer full- and half-sibships even with high error rates. 2. **Iterative Procedure**: The method uses an iterative procedure to update allele frequencies, improving the accuracy of relationship inference. 3. **Parental Genotype Inference**: The method also allows for the inference of parental genotypes, which can be crucial for understanding the mating system and social behavior of species. 4. **Error Detection**: The method can identify typing errors at each locus within each reconstructed sib family, enhancing the reliability of the results. 5. **Empirical Application**: The proposed methods are applied to two empirical data sets to infer sibship structures and mating systems, demonstrating their practical utility. The article emphasizes the importance of accounting for typing errors in sibship reconstruction, as ignoring them can lead to severe biases in relationship inference. The simulations show that the new method can handle high error rates and provide accurate estimates, making it a valuable tool for researchers in behavioral, ecological, and evolutionary genetics.