Test difference between means of entire collection (EC) and core set (CS) for quantitative traits by Newman-Keuls or Student-Newman-Keuls test (Newman 1939; Keuls 1952) .
snk.evaluate.core(data, names, quantitative, selected)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.
Name of column with the individual names as a character string.
Name of columns with the quantitative traits as a character vector.
Character vector with the names of individuals selected in
core collection and present in the names column.
A data frame with the following components.
The quantitative trait.
The minimum value of the trait in EC.
The maximum value of the trait in EC.
The mean value of the trait in EC.
The standard error of the trait in EC.
The minimum value of the trait in CS.
The maximum value of the trait in CS.
The mean value of the trait in CS.
The standard error of the trait in CS.
The p value of the Student-Newman-Keuls test for equality of means of EC and CS.
The significance of the Student-Newman-Keuls test for equality of means of EC and CS.
Keuls M (1952).
“The use of the ,,studentized range" in connection with an analysis of variance.”
Euphytica, 1(2), 112–122.
Newman D (1939).
“The distribution of range in samples from a normal population, expressed in terms of an independent estimate of standard deviation.”
Biometrika, 31(1-2), 20–30.
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)))
snk.evaluate.core(data = ec, names = "genotypes",
quantitative = quant, selected = core)
#> Trait EC_Min EC_Max EC_Mean EC_SE CS_Min CS_Max CS_Mean CS_SE
#> 1 NMSR 1.00 55.00 11.722090 0.18731651 1.00 55.00 10.892857 0.6314310
#> 2 TTRN 0.25 13.75 3.853909 0.04656232 0.25 13.75 3.930655 0.1754066
#> 3 TFWSR 0.00 40.00 5.428979 0.11045567 0.20 38.00 6.348214 0.4696134
#> 4 TTRW 0.00 20.20 1.897948 0.04037796 0.10 20.20 2.617817 0.2207393
#> 5 TFWSS 0.20 42.00 6.943052 0.14359496 0.20 42.00 7.748214 0.5588314
#> 6 TTSW 0.04 22.00 2.387502 0.04878843 0.10 22.00 3.069087 0.2381436
#> 7 TTPW 0.40 80.00 12.372031 0.23851356 0.40 80.00 14.096429 0.9720528
#> 8 AVPW 0.20 33.00 4.285450 0.08195995 0.20 33.00 5.686905 0.4210897
#> 9 ARSR 0.00 18.00 1.858076 0.05493488 0.00 8.00 1.702381 0.1516377
#> 10 SRDM 0.50 48.90 37.771021 0.12264395 21.90 48.10 37.730357 0.3289992
#> SNK_pvalue SNK_significance
#> 1 0.1852 ns
#> 2 0.6261 ns
#> 3 0.0156 *
#> 4 0.0000 **
#> 5 0.0989 ns
#> 6 0.0001 **
#> 7 0.0345 *
#> 8 0.0000 **
#> 9 0.3882 ns
#> 10 0.9194 ns