Hello,
I used Monmonier's difference algorithm to assess its genetic discontinuities based on the Euclidean distance of genetic dataset and geographical coordinates of populations, using the monmonier function of the R adegenet package. The Gabriel graph was used to construct connection network for species populations using the chooseCN function. To reduce noise, I performed a principal component analysis (PCA) for the Euclidean distance of genetic data using the dudi.pco function in the R ade4, whose first eigenvalue was further adopted for the Monmonier algorithm. Now I need to see how stable such identified barriers are. A bootstrap approach should be used, i.e., running the analysis over XY bootstrap replicates.
Does anyone know how the monmonier function in adegenet R package runs over bootstrap pseudo-datasets? With which package and function of R?
Your best course Is to contact the package coordinator. This person can be found in the introduction information for the CRAN pdf describing the package. This person should be able to answer your question.
The information you need can be found from the attached screenshot. Best wishes David Booth
Dear prof. Booth,
Many thanks for your answer.
I have read the adegenet R package. I only suffer to prepare the bootstraps for genetic distances and use it for monmonier function and find the barriers. I have no clue how to do it.
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