Import presence/absence data from SilicoDArT to genlight {agegenet} format (ploidy=1)
DaRT provide the data as a matrix of entities (individual animals) across the top and attributes (P/A of sequenced fragment) down the side in a format that is unique to DArT. This program reads the data in to adegenet format for consistency with other programming activity. The script may require modification as DArT modify their data formats from time to time.
gl.read.silicodart( filename, ind.metafile = NULL, nas = "-", topskip = NULL, lastmetric = "Reproducibility", probar = TRUE, verbose = NULL )
filename |
– name of csv file containing the SilicoDArT data [required] |
ind.metafile |
– name of csv file containing metadata assigned to each entity (individual) [default NULL] |
nas |
– missing data character [default "-"] |
topskip |
– number of rows to skip before the header row (containing the specimen identities) [optional] |
lastmetric |
– specifies the last non genetic column (Default is "Reproducibility"). Be sure to check if that is true, otherwise the number of individuals will not match. You can also specify the last column by a number. [default Reproducibility] |
probar |
show progress bar |
verbose |
– verbosity: 0, silent or fatal errors; 1, begin and end; 2, progress log ; 3, progress and results summary; 5, full report [default 2, or as set by gl.set.verbose()] |
gl.read.silicodart() opens the data file (csv comma delimited) and skips the first n=topskip lines. The script assumes that the next line contains the entity labels (specimen ids) followed immediately by the SNP data for the first locus. It reads the presence/absence data into a matrix of 1s and 0s, and inputs the locus metadata and specimen metadata. The locus metadata comprises a series of columns of values for each locus including the essential columns of CloneID and the desirable variables Reproducibility and PIC. Refer to documentation provide by DArT for an explanation of these columns.
The specimen metadata provides the opportunity to reassign specimens to populations, and to add other data relevant to the specimen. The key variables are id (specimen identity which must be the same and in the same order as the SilicoDArT file, each unique), pop (population assignment), lat (latitude, optional) and lon (longitude, optional). id, pop, lat, lon are the column headers in the csv file. Other optional columns can be added.
The data matrix, locus names (forced to be unique), locus metadata, specimen names, specimen metadata are combined into a genInd object. Refer to the documentation for {adegenet} for further details.
An object of class genlight with ploidy set to 1, containing the presence/absence data, and locus and individual metadata
Bernd Gruber and Arthur Georges (Post to https://groups.google.com/d/forum/dartr)
silicodartfile <- system.file("extdata","testset_SilicoDArT.csv", package="dartR")
metadata <- system.file("extdata",ind.metafile ="testset_metadata_silicodart.csv", package="dartR")
testset.gs <- gl.read.silicodart(filename = silicodartfile, ind.metafile = metadata)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.