Plot Bar plots to graphically compare the frequency distributions of qualitative traits between entire collection (EC) and core set (CS).

bar.evaluate.core(data, names, qualitative, 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.

qualitative

Name of columns with the qualitative 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 relative frequency bar plots of CS and EC for each trait specified as qualitative.

See also

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)))

bar.evaluate.core(data = ec, names = "genotypes",
                  qualitative = qual, selected = core)
#> $CUAL
#> Warning: The dot-dot notation (`..prop..`) was deprecated in ggplot2 3.4.0.
#>  Please use `after_stat(prop)` instead.
#>  The deprecated feature was likely used in the EvaluateCore package.
#>   Please report the issue at
#>   <https://github.com/aravind-j/EvaluateCore/issues>.

#> 
#> $LNGS

#> 
#> $PTLC

#> 
#> $DSTA

#> 
#> $LFRT

#> 
#> $LBTEF

#> 
#> $CBTR

#> 
#> $NMLB

#> 
#> $ANGB

#> 
#> $CUAL9M

#> 
#> $LVC9M

#> 
#> $TNPR9M

#> 
#> $PL9M

#> 
#> $STRP

#> 
#> $STRC

#> 
#> $PSTR

#>