ABSTRACT
Amplified fragment length polymorphism (AFLP), a widely used method for DNA fingerprinting, has shifted from polyacrylamide gel to capillary electrophoresis over the last years. Currently, most AFLP data are generated in a computer-readable format, and several programs are available that automatically score raw data into binary profiles. Good scoring parameters are the key to good AFLP profiles. optiFLP is the first open source program for automatic optimization of AFLP scoring parameters. It searches parameter space to maximize the contrast among groups of AFLP profiles, with the allocation of profiles to groups in either a supervised or an unsupervised mode. The software produces output files ready for use in a range of downstream applications.
Subject(s)
Algorithms , Amplified Fragment Length Polymorphism Analysis/methods , DNA Fingerprinting/methods , Models, Genetic , SoftwareABSTRACT
Amplified fragment length polymorphism (AFLP) is a well-established method for DNA fingerprinting. In the last years, fragment separation gradually changed from using gel to capillary electrophoresis, resulting in large, digital data sets. Automatic scoring softwares available to date are proprietary and expensive. tinyFLP/tinyCAT is a compact, open-source software for automatic scoring of AFLP data. It reads from PeakScanner(©) generated tables, optimizes the conversion of peak data into a binary allelic matrix and removes operator-mediated ambiguities from the scoring process. The output is formatted for direct use in MrBayes and other phylogenetic applications.
