Literature DB >> 25644761

landgenreport: a new r function to simplify landscape genetic analysis using resistance surface layers.

Bernd Gruber1, Aaron T Adamack1.   

Abstract

We describe functions recently added to the r package popgenreport that can be used to perform a landscape genetic analysis (LGA) based on landscape resistance surfaces, which aims to detect the effect of landscape features on gene flow. These functions for the first time implement a LGA in a single framework. Although the approach has been shown to be a valuable tool to study gene flow in landscapes, it has not been widely used to date, despite the type of data being widely available. In part, this is likely due to the necessity to use several software packages to perform landscape genetic analyses. To apply LGA functions, two types of data sets are required: a data set with spatially referenced and genotyped individuals, and a resistance layer representing the effect of the landscape. The function outputs three pairwise distance matrices from these data: a genetic distance matrix, a cost distance matrix and a Euclidean distance matrix. Statistical tests are performed to test whether the cost matrix contributes to the understanding of the observed population structure. A full report on the analysis and outputs in the form of plots and tables of all intermediate steps of the LGA is produced. It is possible to customize the LGA to allow for different cost path approaches and measures of genetic distances. The package is written in the r language and is available through the Comprehensive r Archive. Comprehensive tutorials and information on how to install and use the package are provided at the authors' website (www.popgenreport.org).
© 2015 John Wiley & Sons Ltd.

Keywords:  circuit theory; landscape genetics; least-cost path; population genetics-empirical; resistance surface

Mesh:

Year:  2015        PMID: 25644761     DOI: 10.1111/1755-0998.12381

Source DB:  PubMed          Journal:  Mol Ecol Resour        ISSN: 1755-098X            Impact factor:   7.090


  7 in total

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Authors:  Sara Roose; Russell W Avramenko; Stephen M J Pollo; James D Wasmuth; Shaali Ame; Mio Ayana; Martha Betson; Piet Cools; Daniel Dana; Ben P Jones; Zeleke Mekonnen; Arianna Morosetti; Abhinaya Venkatesan; Johnny Vlaminck; Matthew L Workentine; Bruno Levecke; John S Gilleard; Peter Geldhof
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  7 in total

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