Additional file 2: of An Eigenvalue test for spatial principal component analysis

Example of IbdSettings for IBD_Sim with parameter setting to simulate an isolation by distance evolutionary model. (TXT 635 kb

Additional file 3: Figure S1. of An Eigenvalue test for spatial principal component analysis

Distributions of significant eigenvalues detected in the presence of global (blue bars) and local (green bars) spatial patterns after hierarchical Bonferroni correction, for 100 significantly positive and 100 significantly negative patterns. Black bars correspond to eigenvalues which are significant without Bonferroni correction. Bars’ height indicates the frequency of observing a significant eigenvalue in a certain position (from most positive to most negative) over the 100 tested patterns. (PDF 1150 kb

Additional file 1: of An Eigenvalue test for spatial principal component analysis

Example of GenomePop Input with a parameter setting to simulate an island model of migration. (TXT 363 kb

Supplement 1. Data and R scripts to reproduce the different analyses of the tropical forest data set.

<h2>File List</h2><blockquote> <p><a href="Panama-Analysis.R">Panama-Analysis.R</a></p> <p><a href="pcw.RData">pcw.RData</a></p> </blockquote><h2>Description</h2><blockquote> <p>The file Panama-Analysis.R is an R script allowing to reproduce the analysis of the tropical forest data set. The file pcw.RData contains an R object with the tropical forest data set. It is a list with:</p> <p>- spe: the community data</p> <p>- env: the environmental data</p> <p>- xy.utm: the spatial coordinates (UTM)</p> <p>- map: a map (SpatialPolygons object)</p> <p>- xy: the spatial coordinates (lat-long) for mapping</p> </blockquote