This software accurately predicts the distribution of genotypic data through cline models. It fits data to equilibrium and ensures results are reliable.
ClineFit is an exceptional software that is designed to fit genotypic data to equilibrium cline models pioneered by Nick Barton. One of the many impressive features of ClineFit is its use of a numerical maximum likelihood algorithm (also known as an MCMC method, or a Metropolis-Hastings algorithm, or a biased random walk) that makes estimating maximum-likelihoods and 2-unit support limits an absolute breeze.
With support for diploid, haplodiploid, or sex-linked genotypic data, ClineFit can be used with codominant loci. Additionally, ClineFit accepts data in a format similar to Swofford's BIOSYS or Arlequin format. However, it is important to note that ClineFit requires that the location of each population sample be a number, placed as the last piece of information in the population's name.
To ensure optimal performance, ClineFit requires the identification of the alleles that will be most frequent on the right side of the cline as part of the name of each locus. Overall, ClineFit is a reliable and efficient software solution that makes fitting genotypic data to equilibrium cline models easier than ever before.
With support for diploid, haplodiploid, or sex-linked genotypic data, ClineFit can be used with codominant loci. Additionally, ClineFit accepts data in a format similar to Swofford's BIOSYS or Arlequin format. However, it is important to note that ClineFit requires that the location of each population sample be a number, placed as the last piece of information in the population's name.
To ensure optimal performance, ClineFit requires the identification of the alleles that will be most frequent on the right side of the cline as part of the name of each locus. Overall, ClineFit is a reliable and efficient software solution that makes fitting genotypic data to equilibrium cline models easier than ever before.
What's New
Version 0.1: N/A