LSTM Home > LSTM Research > LSTM Online Archive

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

Rodrigues Antao, Tiago, Lopes, A., Lopes, R. J., Beja-Pereira, A. and Luikart, G. (2008) 'LOSITAN: A workbench to detect molecular adaptation based on a F-st-outlier method'. Bmc Bioinformatics, Vol 9, Issue 323.

Antao-BMC.pdf - Published Version
Available under License Creative Commons Attribution.

Download (377kB)


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.

Item Type: Article
Additional Information: The electronic version of this article is the complete one and can be found online at:
Uncontrolled Keywords: population-structure selection evolution genomics loci
Subjects: QU Biochemistry > QU 26.5 Informatics. Automatic data processing. Computers
QU Biochemistry > Genetics > QU 450 General Works
Faculty: Department: Groups (2002 - 2012) > Molecular & Biochemical Parasitology Group
Digital Object Identifer (DOI):
Depositing User: Mary Creegan
Date Deposited: 23 Aug 2010 12:56
Last Modified: 06 Feb 2018 13:00


View details

Actions (login required)

Edit Item Edit Item