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Relatedness Estimator (relatedness + estimator)
Selected AbstractsEstimation of pairwise relatedness between individuals and characterization of isolation-by-distance processes using dominant genetic markersMOLECULAR ECOLOGY, Issue 6 2003Olivier J. Hardy Abstract A new estimator of the pairwise relatedness coefficient between individuals adapted to dominant genetic markers is developed. This estimator does not assume genotypes to be in Hardy,Weinberg proportions but requires a knowledge of the departure from these proportions (i.e. the inbreeding coefficient). Simulations show that the estimator provides accurate estimates, except for some particular types of individual pairs such as full-sibs, and performs better than a previously developed estimator. When comparing marker-based relatedness estimates with pedigree expectations, a new approach to account for the change of the reference population is developed and shown to perform satisfactorily. Simulations also illustrate that this new relatedness estimator can be used to characterize isolation by distance within populations, leading to essentially unbiased estimates of the neighbourhood size. In this context, the estimator appears fairly robust to moderate errors made on the assumed inbreeding coefficient. The analysis of real data sets suggests that dominant markers (random amplified polymorphic DNA, amplified fragment length polymorphism) may be as valuable as co-dominant markers (microsatellites) in studying microgeographic isolation-by-distance processes. It is argued that the estimators developed should find major applications, notably for conservation biology. [source] TECHNICAL ADVANCES: A maximum-likelihood relatedness estimator allowing for negative relatedness valuesMOLECULAR ECOLOGY RESOURCES, Issue 2 2008DMITRY A. KONOVALOV Abstract Previously reported maximum-likelihood pairwise relatedness (r) estimator of Thompson and Milligan (M) was extended to allow for negative r estimates under the regression interpretation of r. This was achieved by establishing the equivalency of the likelihoods used in the kinship program and the likelihoods of Thompson. The new maximum-likelihood (ML) estimator was evaluated by Monte Carlo simulations. It was found that the new ML estimator became unbiased significantly faster compared to the original M estimator when the amount of genotype information was increased. The effects of allele frequency estimation errors on the new and existing relatedness estimators were also considered. [source] Statistical properties and performance of pairwise relatedness estimators using turbot (Scophthalmus maximus L.) family dataAQUACULTURE RESEARCH, Issue 4 2010Ania Pino-Querido Abstract The statistical properties and performance of four estimators of pairwise relatedness were evaluated in several scenarios using the microsatellite genotype data from a set of large known full-sibships of turbot. All estimators showed a significant negative bias for the four kinships commonly used in these studies (unrelated: UR, half-sibs, full-sibs and parent,offspring), when allele frequencies of the reference population were estimated from the individuals analysed. When these frequencies were obtained from the base population from which all families proceeded, the bias was mostly corrected. The Wang (W) and Li (L) estimators were the least sensitive to this factor, while the Lynch and Ritland (L&R estimator) was the highest one. The error (mean around 0.130) was very similar in all scenarios for W, L and Queller and Goodnight (QG) estimators, while L&R was the highest error-prone estimator. Parent,offspring kinship resulted in the lowest error, when using W, L and QG estimators, while UR resulted in the lowest error with the L&R estimator. Globally, W was the best-performing estimator, although L&R could perform better in specific sampling scenarios. In summary, pairwise estimators represent useful tools for kinship classification in aquaculture broodstock management by applying appropriate thresholds depending on the goals of the analysis. [source] | ||||||||||