EvaluateCore (version 0.1.1)

qq.evaluate.core: Quantile-Quantile Plots

Description

Plot Quantile-Quantile (QQ) plots wilk_probability_1968EvaluateCore to graphically compare the probability distributions of quantitative traits between entire collection (EC) and core set (CS).

Usage

qq.evaluate.core(data, names, quantitative, selected)

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.

Value

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

References

See Also

qqplot

Examples

# NOT RUN {
####################################
# Use data from R package ccChooser
####################################

library(ccChooser)
data("dactylis_CC")
data("dactylis_EC")

ec <- cbind(genotypes = rownames(dactylis_EC), dactylis_EC[, -1])
ec$genotypes <- as.character(ec$genotypes)
rownames(ec) <- NULL
ec[, c("X1", "X6", "X7")] <- lapply(ec[, c("X1", "X6", "X7")],
                                    function(x) cut(x, breaks = 4))
ec[, c("X1", "X6", "X7")] <- lapply(ec[, c("X1", "X6", "X7")],
                                    function(x) factor(as.numeric(x)))
head(ec)

core <- rownames(dactylis_CC)

quant <- c("X2", "X3", "X4", "X5", "X8")
qual <- c("X1", "X6", "X7")

####################################
# EvaluateCore
####################################

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


# }