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This script deletes monomorphic loci from a genlight {adegenet} object

A DArT dataset will not have monomorphic loci, but they can arise, along with loci that are scored all NA, when populations or individuals are deleted.

Retaining monomorphic loci unnecessarily increases the size of the dataset and will affect some calculations.

Note that for SNP data, NAs likely represent null alleles; in tag presence/absence data, NAs represent missing values (presence/absence could not be reliably scored)

Usage

gl.filter.monomorphs(x, verbose = NULL)

Arguments

x

Name of the input genlight object [required].

verbose

Verbosity: 0, silent or fatal errors; 1, begin and end; 2, progress log; 3, progress and results summary; 5, full report [default 2, unless specified using gl.set.verbosity].

Value

A genlight object with monomorphic (and all NA) loci removed.

Author

Custodian: Arthur Georges -- Post to https://groups.google.com/d/forum/dartr

Examples

# SNP data
  result <- gl.filter.monomorphs(testset.gl, verbose=3)
#> Starting gl.filter.monomorphs 
#>   Processing genlight object with SNP data
#>   Identifying monomorphic loci
#>   Removing monomorphic loci and loci with all missing 
#>                        data
#>     Original No. of loci: 255 
#>     Monomorphic loci: 144 
#>     Loci scored all NA: 0 
#>     No. of loci deleted: 144 
#>     No. of loci retained: 111 
#>     No. of individuals: 250 
#>     No. of populations: 30 
#> Completed: gl.filter.monomorphs 
#> 
# Tag P/A data
  result <- gl.filter.monomorphs(testset.gs, verbose=3)
#> Starting gl.filter.monomorphs 
#>   Processing genlight object with Presence/Absence (SilicoDArT) data
#>   Identifying monomorphic loci
#>   Removing monomorphic loci and loci with all missing 
#>                        data
#>     Original No. of loci: 255 
#>     Monomorphic loci: 41 
#>     Loci scored all NA: 0 
#>     No. of loci deleted: 41 
#>     No. of loci retained: 214 
#>     No. of individuals: 218 
#>     No. of populations: 29 
#> Completed: gl.filter.monomorphs 
#>