wilcox.evaluate.core {EvaluateCore} | R Documentation |
Wilcoxon Rank Sum Test
Description
Compare the medians of quantitative traits between entire collection (EC) and core set (CS) by Wilcoxon rank sum test or Mann-Whitney-Wilcoxon test or Mann-Whitney U test (Wilcoxon 1945; Mann and Whitney 1947).
Usage
wilcox.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 |
Value
Trait |
The quantitative trait. |
EC_Med |
The median value of the trait in EC. |
CS_Med |
The median value of the trait in CS. |
Wilcox_pvalue |
The p value of the Wilcoxon test for equality of medians of EC and CS. |
Wilcox_significance |
The significance of the Wilcoxon test for equality of medians of EC and CS. |
References
Mann HB, Whitney DR (1947).
“On a test of whether one of two random variables is stochastically larger than the other.”
The Annals of Mathematical Statistics, 18(1), 50–60.
Wilcoxon F (1945).
“Individual comparisons by ranking methods.”
Biometrics Bulletin, 1(6), 80.
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)))
wilcox.evaluate.core(data = ec, names = "genotypes",
quantitative = quant, selected = core)