Create a table summarizing missing data or ploidy information of a genind or genclone object

Usage

info_table(
  gen,
  type = c("missing", "ploidy"),
  percent = TRUE,
  plot = FALSE,
  df = FALSE,
  returnplot = FALSE,
  low = "blue",
  high = "red",
  plotlab = TRUE,
  scaled = TRUE
)

Arguments

gen: a genind or genclone object.
type: character. What information should be returned. Choices are "missing" (Default) and "ploidy". See Description.
percent: logical. (ONLY FOR type = 'missing') If TRUE (default), table and plot will represent missing data as a percentage of each cell. If FALSE, the table and plot will represent missing data as raw counts. (See details)
plot: logical. If TRUE, a simple heatmap will be produced. If FALSE (default), no heatmap will be produced.
df: logical. If TRUE, the data will be returned as a long form data frame. If FALSE (default), a matrix with samples in rows and loci in columns will be returned.
returnplot: logical. If TRUE, a list is returned with two elements: table - the normal output and plot - the ggplot object. If FALSE, the table is returned.
low: character. What color should represent no missing data or lowest observed ploidy? (default: "blue")
high: character. What color should represent the highest amount of missing data or observed ploidy? (default: "red")
plotlab: logical. (ONLY FOR type = 'missing') If TRUE (default), values of missing data greater than 0% will be plotted. If FALSE, the plot will appear un-appended.
scaled: logical. (ONLY FOR type = 'missing') This is for when percent = TRUE. If TRUE (default), the color specified in high will represent the highest observed value of missing data. If FALSE, the color specified in high will represent 100%.

Value

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.

Details

Missing data is accounted for on a per-population level.
Ploidy is accounted for on a per-individual level.

For type = 'missing'

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.

For type = 'ploidy'

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.

Author

Zhian N. Kamvar

Examples

data(nancycats)
nancy.miss <- info_table(nancycats, plot = TRUE, type = "missing")

data(Pinf)
Pinf.ploid <- info_table(Pinf, plot = TRUE, type = "ploidy")