coverage.evaluate.core: Class Coverage

View source: R/coverage.evaluate.core.R

coverage.evaluate.coreR Documentation

Class Coverage

Description

Compute the Class Coverage \insertCitekim_powercore_2007EvaluateCore to compare the distribution frequencies of qualitative traits between entire collection (EC) and core set (CS). \loadmathjax

Usage

coverage.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.

Details

Class Coverage \insertCitekim_powercore_2007EvaluateCore is computed as follows.

\mjsdeqn

Class\, Coverage = \left ( \frac1n \sum_i=1^n \fracA_CS_iA_EC_i \right ) \times 100

Where, \mjseqnA_CS_i is the sets of categories in the CS for the \mjseqnith trait, \mjseqnA_EC_i is the sets of categories in the EC for the \mjseqnith trait and \mjseqnn is the total number of traits.

Value

The Class Coverage value.

References

\insertAllCited

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)))

coverage.evaluate.core(data = ec, names = "genotypes",
                       qualitative = qual, selected = core)


EvaluateCore documentation built on July 3, 2022, 5:06 p.m.