R/gl.read.dart.r
gl.read.dart.RdThis function is a wrapper function that allows you to convert your DArT file into a genlight object of class dartR.
gl.read.dart(
filename,
ind.metafile = NULL,
recalc = TRUE,
mono.rm = FALSE,
nas = "-",
topskip = NULL,
lastmetric = NULL,
covfilename = NULL,
service.row = 1,
plate.row = 3,
probar = FALSE,
verbose = NULL
)File containing the SNP data (csv file) [required].
File that contains additional information on individuals [required].
If TRUE, force the recalculation of locus metrics [default TRUE].
If TRUE, force the removal of monomorphic loci (including all NAs. [default FALSE].
A character specifying NAs [default '-'].
A number specifying the number of initial rows to be skipped. [default NULL].
Deprecated, specifies the last column of locus metadata. Can be specified as a column number [default NULL].
Deprecated, sse ind.metafile parameter [NULL].
The row number for the DArT service is contained [default 1].
The row number the plate well [default 3].
Show progress bar [default FALSE].
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()].
A dartR genlight object that contains individual and locus metrics [if data were provided] and locus metrics [from a DArT report].
The function will determine automatically if the data are in Diversity Arrays one-row csv format or two-row csv format.
The first row of data is determined from the number of rows with an * in the first column. This can be alternatively specified with the topskip parameter.
The DArT service code is added to the ind.metrics of the genlight object. The row containing the service code for each individual can be specified with the service.row parameter.
#'The DArT plate well is added to the ind.metrics of the genlight object. The row containing the plate well for each individual can be specified with the plate.row parameter.
If individuals have been deleted from the input file manually, then the locus metrics supplied by DArT will no longer be correct and some loci may be monomorphic. To accommodate this, set mono.rm and recalc to TRUE.
Other dartR-base:
gl.drop.ind(),
gl.drop.loc(),
gl.drop.pop(),
gl.edit.recode.ind(),
gl.edit.recode.pop(),
gl.keep.loc(),
gl.make.recode.ind(),
gl.recode.ind(),
gl.recode.pop(),
gl.set.verbosity()
dartfile <- system.file('extdata','testset_SNPs_2Row.csv', package='dartR')
metadata <- system.file('extdata','testset_metadata.csv', package='dartR')
gl <- gl.read.dart(dartfile, ind.metafile = metadata, probar=TRUE)
#> Starting gl.read.dart
#> Starting utils.read.dart
#> Topskip not provided.
#> Setting topskip to 3 .
#> Reading in the SNP data
#> Detected 2 row format.
#> Number of rows per clone (should be only 2 s): 2
#> Added the following locus metrics:
#> AlleleID CloneID AlleleSequence SNP SnpPosition CallRate OneRatioRef OneRatioSnp TrimmedSequence FreqHomRef FreqHomSnp FreqHets PICRef PICSnp AvgPIC AvgCountRef AvgCountSnp RepAvg .
#> Recognised: 250 individuals and 255 SNPs in a 2 row format using /home/runner/work/_temp/Library/dartR/extdata/testset_SNPs_2Row.csv
#> Completed: utils.read.dart
#> Starting utils.dart2genlight
#> Starting conversion....
#> Format is 2 rows.
#> Please note conversion of bigger data sets will take some time!
#> Once finished, we recommend to save the object using save(object, file="object.rdata")
#>
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#> Adding individual metrics: /home/runner/work/_temp/Library/dartR/extdata/testset_metadata.csv .
#> Ids for individual metadata (at least a subset of) are matching!
#> Found 250 matching ids out of 250 ids provided in the ind.metadata file.
#> Added population assignments.
#> Added latlon data.
#> Added id to the other$ind.metrics slot.
#> Added pop to the other$ind.metrics slot.
#> Added lat to the other$ind.metrics slot.
#> Added lon to the other$ind.metrics slot.
#> Added sex to the other$ind.metrics slot.
#> Added maturity to the other$ind.metrics slot.
#> Completed: utils.dart2genlight
#> 250 rows and 255 columns of data read
#> Read depth calculated and added to the locus metrics
#> Minor Allele Frequency (MAF) calculated and added to the locus metrics
#> Recalculating locus metrics provided by DArT (optionally specified)
#> Starting gl.compliance.check
#> Processing genlight object with SNP data
#> Checking coding of SNPs
#> SNP data scored NA, 0, 1 or 2 confirmed
#> Checking locus metrics and flags
#> Recalculating locus metrics
#> Checking for monomorphic loci
#> Dataset contains monomorphic loci
#> Checking for loci with all missing data
#> No loci with all missing data detected
#> Checking whether individual names are unique.
#> Checking for individual metrics
#> Individual metrics confirmed
#> Checking for population assignments
#> Population assignments confirmed
#> Spelling of coordinates checked and changed if necessary to
#> lat/lon
#> Completed: gl.compliance.check
#> Completed: gl.read.dart
#>