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

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.


Publié dans:
arXiv Quantitative Biology, [q-bio.PE], arXiv:1405.7658v1
Année
2014
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 Notice créée le 2014-05-30, modifiée le 2019-03-24

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