R: Export analysis for mvmapper visualisation

export_to_mvmapper {adegenet} | R Documentation

## Export analysis for mvmapper visualisation

### Description

`mvmapper` is an interactive tool for visualising outputs of a multivariate analysis on a map from a web browser. The function `export_to_mvmapper` is a generic with methods for several standard classes of analyses in `adegenet` and `ade4`. Information on individual locations, as well as any other relevant data, is passed through the second argument `info`. By default, the function returns a formatted `data.frame` and writes the output to a .csv file.

### Usage

    export_to_mvmapper(x, ...)

    ## Default S3 method:
    export_to_mvmapper(x, ...)

    ## S3 method for class 'dapc'
    export_to_mvmapper(x, info, write_file = TRUE, out_file = NULL, ...)

    ## S3 method for class 'dudi'
    export_to_mvmapper(x, info, write_file = TRUE, out_file = NULL, ...)

    ## S3 method for class 'spca'
    export_to_mvmapper(x, info, write_file = TRUE, out_file = NULL, ...)

### Arguments

`x` | The analysis to be exported. Can be a `dapc`, `spca`, or a `dudi` object.
`...` | Further arguments to pass to other methods.
`info` | A `data.frame` with additional information containing at least the following columns: `key` (unique individual identifier), `lat` (latitude), and `lon` (longitude). Other columns will be exported as well, but are optional.
`write_file` | A `logical` indicating if the output should be written out to a .csv file. Defaults to `TRUE`.
`out_file` | A character string indicating the file to which the output should be written. If NULL, the file used will be named `'mvmapper_data_[date and time].csv'`

### Details

`mvmapper` can be found at: https://popphylotools.github.io/mvMapper/

### Value

A `data.frame` which can serve as input to `mvmapper`, containing at least the following columns:

- `key`: unique individual identifiers

- `PC1`: first principal component; further principal components are optional, but if provided will be numbered and follow `PC1`.

- `lat`: latitude for each individual

- `lon`: longitude for each individual

In addition, specific information is added for some analyses:

- `spca`: `Lag_PC` columns contain the lag-vectors of the principal components; the lag operator computes, for each individual, the average score of neighbouring individuals; it is useful for clarifying patches and clines.

- `dapc`: `grp` is the group used in the analysis; `assigned_grp` is the group assignment based on the discriminant functions; `support` is the statistical support (i.e. assignment probability) for `assigned_grp`.

### Author(s)

Thibaut Jombart thibautjombart@gmail.com

### See Also

`mvmapper` is available at: https://popphylotools.github.io/mvMapper/

### Examples

    # An example using the microsatellite dataset of Dupuis et al. 2016 (781
    # individuals, 10 loci, doi: 10.1111/jeb.12931)

    # Reading input file from adegenet

    input_data <- system.file("data/swallowtails.rda", package="adegenet")
    data(swallowtails)

    # conducting a DAPC (n.pca determined using xvalDapc, see ??xvalDapc)

    dapc1 <- dapc(swallowtails, n.pca=40, n.da=200)

    # read in swallowtails_loc.csv, which contains "key", "lat", and "lon"
    # columns with column headers (this example contains additional columns
    # containing species identifications, locality descriptions, and COI
    # haplotype clades)

    input_locs <- system.file("files/swallowtails_loc.csv", package = "adegenet")
    loc <- read.csv(input_locs, header = TRUE)

    # generate mvmapper input file, automatically write the output to a csv, and
    # name the output csv "mvMapper_Data.csv"
    out_dir <- tempdir()
    out_file <- file.path(out_dir, "mvMapper_Data.csv")

    out <- export_to_mvmapper(dapc1, loc, write_file = TRUE, out_file = out_file)

[Package adegenet version 2.1.4 Index]