Software

LOSITAN: A workbench to detect molecular adaptation based on a F_st-outlier method

Tiago Antao¹ , Ana Lopes² , Ricardo J Lopes³ , Albano Beja-Pereira³ and Gordon Luikart^3,4

¹Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UK

²REQUIMTE, Departamento de Química, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, 687, 4169-007 Porto, Portugal

³CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Campus Agrário de Vairão, Universidade do Porto, Portugal

⁴Division of Biological Sciences, University of Montana, Missoula, MT 59812, USA

author email corresponding author email

BMC Bioinformatics 2008, 9:323doi:10.1186/1471-2105-9-323

Published:	28 July 2008

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 F_st-outlier detection method. LOSITAN greatly facilitates correct approximation of model parameters (e.g., genome-wide average, neutral F_st), 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.