DaRT provide the data as a matrix of entities (individual turtles) across the top and attributes (SNP loci) down the side in a format that is unique to DArT. This program reads the data in to adegenet format (genlight) for consistency with other programming activity. The script or the data may require modification as DArT modify their data formats from time to time.
gl.read.dart.2row(datafile, topskip, nmetavar, nas = "-",
ind.metafile = NULL, pbar = TRUE, v = 2)-- name of csv file containing the DartSeq data in 2-row format (csv) [required]
-- number of rows to skip before the header row (containing the specimen identities [required]
-- number of columns containing the locus metadata (e.g. AlleleID, RepAvg) [required]
-- missing data character [default "-"]
-- name of csv file containing metadata assigned to each entity (individual) [default NULL]
-- display progress bar [FALSE]
-- verbosity: 0, silent or fatal errors; 1, begin and end; 2, progress log ; 3, progress and results summary; 5, full report [default 2]
An object of class ("genlight") containing the SNP data, and locus and individual metadata
gl.read.dart() 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 SNP 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 AlleleID, SNP, SnpPostion and the desirable variables REpAvg and AvgPIC. 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 DArTSeq 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 SNP matrix, locus names (constructed from the AlleleID, SNP and SnpPosition to be unique), locus metadata, specimen names, specimen metadata are combined into a genlight object. Refer to the genlight documentation (Package adegenet) for further details.
# NOT RUN {
gl <- gl.read.dart.2row(datafile="SNP_DFwt15-1908_scores_2Row.csv", topskip=6,
nmetavar=16, nas="-", ind.metafile="metadata.csv" )
# }
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