View source: R/gl.filter.reproducibility.r
gl.filter.reproducibility | R Documentation |
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.
SilicoDArT datasets generated by DArT have a similar index, Reproducibility. For these fragment presence/absence data, repeatability is the percentage of scores that are repeated in the technical replicate dataset.
gl.filter.reproducibility(
x,
threshold = 0.99,
plot.out = TRUE,
plot_theme = theme_dartR(),
plot_colors = two_colors,
save2tmp = FALSE,
verbose = NULL
)
x |
Name of the genlight object containing the SNP data [required]. |
threshold |
Threshold value below which loci will be removed [default 0.99]. |
plot.out |
If TRUE, displays a plots of the distribution of reproducibility values before and after filtering [default TRUE]. |
plot_theme |
Theme for the plot [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]. |
Returns a genlight object retaining loci with repeatability (Repavg or Reproducibility) greater than the specified threshold.
Custodian: Arthur Georges – Post to https://groups.google.com/d/forum/dartr
gl.report.reproducibility
Other filter functions:
gl.filter.allna()
,
gl.filter.callrate()
,
gl.filter.heterozygosity()
,
gl.filter.hwe()
,
gl.filter.ld()
,
gl.filter.locmetric()
,
gl.filter.maf()
,
gl.filter.monomorphs()
,
gl.filter.overshoot()
,
gl.filter.parent.offspring()
,
gl.filter.pa()
,
gl.filter.rdepth()
,
gl.filter.secondaries()
,
gl.filter.sexlinked()
,
gl.filter.taglength()
# SNP data
gl.report.reproducibility(testset.gl)
result <- gl.filter.reproducibility(testset.gl, threshold=0.99, verbose=3)
# Tag P/A data
gl.report.reproducibility(testset.gs)
result <- gl.filter.reproducibility(testset.gs, threshold=0.99)
test <- gl.subsample.loci(platypus.gl,n=100)
res <- gl.filter.reproducibility(test)
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