box.evaluate.core: Box Plots

In EvaluateCore: Quality Evaluation of Core Collections

Box Plots

Description

Plot Box-and-Whisker plots \insertCitetukey_exploratory_1970,mcgill_variations_1978EvaluateCore to graphically compare the probability distributions of quantitative traits between entire collection (EC) and core set (CS).

Usage

box.evaluate.core(data, names, quantitative, selected, show.count = FALSE)

Arguments

data	The data as a data frame object. The data frame should possess one row per individual and columns with the individual names and multiple trait/character data.
names	Name of column with the individual names as a character string.
quantitative	Name of columns with the quantitative traits as a character vector.
selected	Character vector with the names of individuals selected in core collection and present in the names column.
show.count	logical. If TRUE, the accession count excluding missing values will also be displayed. Default is FALSE.

Value

A list with the ggplot objects of box plots of CS and EC for each trait specified as quantitative.

References

\insertAllCited

See Also

boxplot, geom_boxplot

Examples

data("cassava_CC")
data("cassava_EC")

ec <- cbind(genotypes = rownames(cassava_EC), cassava_EC)
ec$genotypes <- as.character(ec$genotypes)
rownames(ec) <- NULL

core <- rownames(cassava_CC)

quant <- c("NMSR", "TTRN", "TFWSR", "TTRW", "TFWSS", "TTSW", "TTPW", "AVPW",
           "ARSR", "SRDM")
qual <- c("CUAL", "LNGS", "PTLC", "DSTA", "LFRT", "LBTEF", "CBTR", "NMLB",
          "ANGB", "CUAL9M", "LVC9M", "TNPR9M", "PL9M", "STRP", "STRC",
          "PSTR")

ec[, qual] <- lapply(ec[, qual],
                     function(x) factor(as.factor(x)))


box.evaluate.core(data = ec, names = "genotypes",
                  quantitative = quant, selected = core)

box.evaluate.core(data = ec, names = "genotypes",
                  quantitative = quant, selected = core, show.count = TRUE)

EvaluateCore documentation built on April 22, 2026, 9:07 a.m.