This web site contains various computer programs developed by biometrics staff within Fisheries and Ecological Services. All materials are available without charge. Additional programs and updated versions of current programs may be available periodically. If you would like to be notified of the posting of an updated version, send an e-mail message with your e-mail address and the program(s) you are using to firstname.lastname@example.org
All files available on this site have been scanned for viruses with current virus detection software. An attempt has been made to make these programs as error-free as possible. However, as with any software, errors may persist. If any errors are discovered, please send the data file and a description of the error to email@example.com. No warranty regarding the correctness or reliability of any materials available on this site is provided, and no liability is assumed by the authors or by USFWS. Any risk associated with the use of any materials available on this site is borne solely by the user. Access of any material available on this site constitutes your acceptance of any such risks.
For Information regarding programs developed prior to 2009, please contact Jeff Bromaghin at firstname.lastname@example.org
KSSim conducts a Kolmogorov-Smirnov test of the null hypothesis that the distributions of multiple populations are equal versus the global alternative that at least two distributions differ. The p-value of the test statistic is estimated using Monte Carlo simulation, which is almost always preferable to an asymptotic approximation. Several options for program control and output are available.
Use of polymorphic DNA loci is increasingly common in genetic studies of natural resources. DNA loci often possess a large number of relatively rare alleles. In typically sized samples, rare alleles may be unobserved or observed infrequently. Although a common strategy for dealing with rare alleles is to bin alleles, an objective method for doing so has only recently become available. OptiBin implements the allele binning algorithm of Bromaghin and Crane (2005), and its use is described by Bromaghin (2006).
Bromaghin, J. F. 2006. OptiBin: a computer program to bin alleles similarly distributed across populations. Molecular Ecology Notes 6: 573-575.
Bromaghin, J. F., and P. A. Crane. 2005. A method to bin alleles of genetic loci that maintains population heterogeneity. Canadian Journal of Fisheries and Aquatic Sciences. 62: 1570-1579
The number of genetic loci available for some species exceeds the number that is either practical or recommended in studies of mixture composition or individual origination. Methods commonly used to select or rank genetic loci for use in such studies are largely based on single-locus genetic distance or performance measures. Synergisms between loci are not exploited. In addition, available locus-selection methods do not exploit the fact that estimation to the level of individual populations is often not required. BELS implements a backward-elimination, locus-selection algorithm. Starting with a complete baseline, loci are sequentially excluded from the baseline in the order which results in the smallest decrease in baseline performance. Program execution terminates when the baseline contains a single remaining locus or when a minimum desired level of performance can not be maintained if additional loci are eliminated. Numerous options for measuring baseline performance and controlling stochasticity are available.
Note: the version of BELS available on this site will run on any 32-bit processor, but is optimized for a dual-core processor.
Bromaghin, J. F. 2008. BELS: backward elimination locus selection for studies of mixture composition or individual assignment. Molecular Ecology Resources 8: 568-571.
Last updated: September 1, 2009