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dartR (version 2.0.4)

gl.report.reproducibility: Reports summary of RepAvg (repeatability averaged over both alleles for each locus) or reproducibility (repeatability of the scores for fragment presence/absence)

Description

SNP datasets generated by DArT have an index, RepAvg, generated by reproducing the data independently for 30 of alleles that give a repeatable result, averaged over both alleles for each locus.

In the case of fragment presence/absence data (SilicoDArT), repeatability is the percentage of scores that are repeated in the technical replicate dataset.

Usage

gl.report.reproducibility(
  x,
  plot.out = TRUE,
  plot_theme = theme_dartR(),
  plot_colors = two_colors,
  save2tmp = FALSE,
  verbose = NULL
)

Arguments

x

Name of the genlight object containing the SNP or presence/absence (SilicoDArT) data [required].

plot.out

If TRUE, displays a plot to guide the decision on a filter threshold [default TRUE].

plot_theme

Theme for the plot. See Details for options [default theme_dartR()].

plot_colors

List of two color names for the borders and fill of the plots [default two_colors].

save2tmp

If TRUE, saves any ggplots and listings to the session temporary directory (tempdir) [default FALSE].

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

An unaltered genlight object

Details

The function displays a table of minimum, maximum, mean and quantiles for repeatbility against possible thresholds that might subsequently be specified in gl.filter.reproducibility.

If plot.out=TRUE, display also includes a boxplot and a histogram to guide in the selection of a threshold for filtering on repeatability.

If save2tmp=TRUE, ggplots and relevant tabulations are saved to the session's temp directory (tempdir)

For examples of themes, see:

See Also

gl.filter.reproducibility

Other filters and filter reports: gl.filter.allna(), gl.filter.monomorphs(), gl.filter.rdepth(), gl.filter.reproducibility(), gl.filter.secondaries(), gl.report.callrate(), gl.report.hamming(), gl.report.locmetric(), gl.report.monomorphs(), gl.report.rdepth(), gl.report.taglength()

Examples

Run this code
# NOT RUN {
# SNP data
  out <- gl.report.reproducibility(testset.gl)
# Tag P/A data
  out <- gl.report.reproducibility(testset.gs)

# }

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