High performance computation of landscape genomic models integrating local indices of spatial association


High performance computation of landscape genomic models integrating local indices of spatial association

Sylvie Stucki, Pablo Orozco-terWengel, Michael W. Bruford, Licia Colli, Charles Masembe, Riccardo Negrini, Pierre Taberlet, Stéphane Joost, the NEXTGEN Consortium
Comments: 1 figure in text, 1 figure in supplementary material
Subjects: Populations and Evolution (q-bio.PE)

Motivation: The increasing availability of high-throughput datasets requires powerful methods to support the detection of signatures of selection in landscape genomics. Results: We present an integrated approach to study signatures of local adaptation, providing rapid processing of whole genome data and enabling assessment of spatial association using molecular markers. Availabilty: Sam{\ss}ada is an open source software written in C++ available at http:lasig.epfl.ch/sambada (under the license GNU GPL 3). Compiled versions are provided for Windows, Linux and MacOS X. Contact: stephane.joost@epfl.ch, sylvie.stucki@a3.epfl.ch. Supplementary material is available online.

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