View source: R/visualizations.r
info_table | R Documentation |
Create a table summarizing missing data or ploidy information of a genind or genclone object
info_table(
gen,
type = c("missing", "ploidy"),
percent = TRUE,
plot = FALSE,
df = FALSE,
returnplot = FALSE,
low = "blue",
high = "red",
plotlab = TRUE,
scaled = TRUE
)
gen |
a genind or genclone object. |
type |
|
percent |
|
plot |
|
df |
|
returnplot |
|
low |
|
high |
|
plotlab |
|
scaled |
|
Missing data is accounted for on a per-population level.
Ploidy is accounted for on a per-individual level.
This data is potentially useful for identifying areas of systematic missing data. There are a few caveats to be aware of.
Regarding counts of missing data: Each count represents the number of individuals with missing data at each locus. The last column, "mean" can be thought of as the average number of individuals with missing data per locus.
Regarding percentage missing data: This percentage is relative to the population and locus, not to the entire data set. The last column, "mean" represents the average percent of the population with missing data per locus.
This option is useful for data that has been imported with mixed ploidies. It will summarize the relative levels of ploidy per individual per locus. This is simply based off of observed alleles and does not provide any further estimates.
a matrix, data frame (df = TRUE
), or a list (returnplot
= TRUE
) representing missing data per population (type = 'missing'
)
or ploidy per individual (type = 'ploidy'
) in a genind
or genclone object.
Zhian N. Kamvar
data(nancycats)
nancy.miss <- info_table(nancycats, plot = TRUE, type = "missing")
data(Pinf)
Pinf.ploid <- info_table(Pinf, plot = TRUE, type = "ploidy")
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