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BMC Bioinformatics. 2008 Jul 28;9:323. doi: 10.1186/1471-2105-9-323.

LOSITAN: a workbench to detect molecular adaptation based on a Fst-outlier method.

Author information

  • 1Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UK. tiago.antao@liverpool.ac.uk

Abstract

BACKGROUND:

Testing for selection is becoming one of the most important steps in the analysis of multilocus population genetics data sets. Existing applications are difficult to use, leaving many non-trivial, error-prone tasks to the user.

RESULTS:

Here we present LOSITAN, a selection detection workbench based on a well evaluated Fst-outlier detection method. LOSITAN greatly facilitates correct approximation of model parameters (e.g., genome-wide average, neutral Fst), provides data import and export functions, iterative contour smoothing and generation of graphics in a easy to use graphical user interface. LOSITAN is able to use modern multi-core processor architectures by locally parallelizing fdist, reducing computation time by half in current dual core machines and with almost linear performance gains in machines with more cores.

CONCLUSION:

LOSITAN makes selection detection feasible to a much wider range of users, even for large population genomic datasets, by both providing an easy to use interface and essential functionality to complete the whole selection detection process.

PMID:
18662398
[PubMed - indexed for MEDLINE]
PMCID:
PMC2515854
Free PMC Article

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