Population Genetics for Animal Conservation 2001
DOI: 10.1017/cbo9780511626920.003
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Statistical methods for identifying hybrids and groups

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Cited by 9 publications
(9 citation statements)
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“…Because the power of detection of late hybrid generations is limited3435 we did not attempted to distinguish those different classes and treated them in this study as a single group of late-hybrids36. A considerable amount of genetic data is required to distinguish genealogical classes and it is very difficult to accurately resolve further genealogical classes or second-backcrossed hybrids with NEWHYBRIDS or any other Bayesian Program37. NEWHYBRIDS analyses were based on the same computational parameters as those conducted in STRUCTURE using a threshold of q  = 0.90.…”
Section: Methodsmentioning
confidence: 99%
“…Because the power of detection of late hybrid generations is limited3435 we did not attempted to distinguish those different classes and treated them in this study as a single group of late-hybrids36. A considerable amount of genetic data is required to distinguish genealogical classes and it is very difficult to accurately resolve further genealogical classes or second-backcrossed hybrids with NEWHYBRIDS or any other Bayesian Program37. NEWHYBRIDS analyses were based on the same computational parameters as those conducted in STRUCTURE using a threshold of q  = 0.90.…”
Section: Methodsmentioning
confidence: 99%
“…The identification of hybrids and the ability to determine the presence, types and numbers of individuals of different hybrid classes can provide crucial information on the presence, magnitude and timescale over which introgression is occurring. While several statistical approaches [reviewed by (Anderson ; Payseur & Rieseberg )] and software programs exist [e.g. structure (Hubisz et al .…”
Section: Introductionmentioning
confidence: 99%
“…The identification of hybrids and the ability to determine the presence, types and numbers of individuals of different hybrid classes can provide crucial information on the presence, magnitude and timescale over which introgression is occurring. While several statistical approaches [reviewed by (Anderson 2009;Payseur & Rieseberg 2016)] and software programs exist [e.g. STRUCTURE (Hubisz et al 2009); NEWHYBRIDS (Anderson & Thompson 2002); BAYESASS (Wilson & Rannala 2003); GENODIVE (Meirmans & Van Tienderen 2004), which uses the maximum-likelihood method of (Buerkle 2005)] to identify hybrids, most do not assign to hybrid class, thus losing potentially important information.…”
Section: Introductionmentioning
confidence: 99%
“…The model-based approach described by Anderson and Thompson (2002) and Anderson (2009) and implemented in the program NEWHYBRIDS was used to assign each individual to one of the two parental classes (tule or URB) or to one of several hybrid classes (F 1 , F 2 , or backcross) based on their microsatellite genotypes. This model is similar to other clustering algorithms but also takes into account known patterns of Mendelian inheritance to assign posterior probabilities that each individual in a data set belongs to each potential class.…”
Section: Hybrid Detectionmentioning
confidence: 99%
“…This model is similar to other clustering algorithms but also takes into account known patterns of Mendelian inheritance to assign posterior probabilities that each individual in a data set belongs to each potential class. This model does not require fixed allelic differences between parental classes (Anderson and Thompson 2002); however, analysis of simulated data has been advocated as a means of evaluating assignment accuracy for any given study (Anderson 2009).…”
Section: Hybrid Detectionmentioning
confidence: 99%