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 names column.

### 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.

wilcox.test

### Examples


####################################
# 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)))

core <- rownames(dactylis_CC)

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

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

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



[Package EvaluateCore version 0.1.2 Index]