View source: R/coverage.evaluate.core.R
coverage.evaluate.core | R Documentation |
Compute the Class Coverage \insertCitekim_powercore_2007EvaluateCore to compare the distribution frequencies of qualitative traits between entire collection (EC) and core set (CS). \loadmathjax
coverage.evaluate.core(data, names, qualitative, selected)
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 |
Class Coverage \insertCitekim_powercore_2007EvaluateCore is computed as follows.
\mjsdeqnClass\, 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.
The Class Coverage value.
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)
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