HACSim

Performs iterative extrapolation of species' haplotype accumulation curves using a nonparametric stochastic (Monte Carlo) optimization method for assessment of specimen sampling completeness based on the approach of Phillips et al. (2015) doi:10.1515/dna-2015-0008, Phillips et al. (2019) doi:10.1002/ece3.4757 and Phillips et al. (2020) doi:10.7717/peerj-cs.243. 'HACSim' outputs a number of useful summary statistics of sampling coverage ("Measures of Sampling Closeness"), including an estimate of the likely required sample size (along with desired level confidence intervals) necessary to recover a given number/proportion of observed unique species' haplotypes. Any genomic marker can be targeted to assess likely required specimen sample sizes for genetic diversity assessment. The method is particularly well-suited to assess sampling sufficiency for DNA barcoding initiatives. Users can also simulate their own DNA sequences according to various models of nucleotide substitution. A Shiny app is also available.

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