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samβada is a genome-environment association software, designed to search for signatures of local adaptation. However, pre- and postprocessing of data can be labour-intensive, preventing wider uptake of the method. We have now developed R.SamBada, an r-package providing a pipeline for landscape genomic analysis based on samβada, spanning from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, R.SamBada standardizes the landscape genomics pipeline and eases the search for candidate genes of local adaptation, enhancing reproducibility of landscape genomic studies. The efficiency and power of the pipeline is illustrated using two examples: sheep populations from Morocco with no evident population structure and Lidia cattle from Spain displaying population substructuring. In both cases, R.SamBada enabled rapid identification and interpretation of candidate genes, which are further discussed in the light of local adaptation. The package is available in the r CRAN package repository and on GitHub (github.com/SolangeD/R.SamBada).
Pubmed ID: 31136078
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Data analysis service to predict the functional consequences of known and unknown variants.
View all literature mentionsA set of global climate layers (climate grids) with a spatial resolution of about 1 square kilometer. The data can be used for mapping and spatial modeling in a GIS or with other computer programs. If you are not familiar with such programs, you can try DIVA-GIS or the R raster package.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17,2022. Genome databases for vertebrates and other eukaryotic species. Analysis and annotation maintained on current data.Distribution of analysis to other bioinformatics laboratories. Ensembl concentrates on vertebrate genomes, but other groups have adapted system for use with plant and fungal genomes (see Powered by Ensembl list on website).
View all literature mentionsInformational portal that aggregates information about databases for next gen sequencing.
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