Compute and transform relative frequencies or accessions for a qualitative trait by the following methods (Balakrishnan and Suresh 2001) :
Square root-proportion
Log-frequency
Usage
prop.adj(x, method = c("none", "log", "sqrt"))
Details
If \(p_{i}\) is the relative frequency of the \(i\)th descriptive state for a qualitative trait in a collection, then the square root-proportion transformed relative \(q_{i}\) is computed as
\[q_{i} = \frac{\sqrt{p_{i}}}{\sum_{i=1}^{s}\sqrt{p_{i}}}\]
Where \(s\) is the number of possible descriptor states for the qualitative trait in the collection.
Similarly, the log-frequency transformed relative \(q_{i}\) is computed as \[q_{i} = \frac{\log{F_{i}}}{\sum_{i=1}^{s}\log{F_{i}}}\]
Where \(F_{i}\) is the absolute frequency of the \(i\)th descriptive state for a qualitative trait in a collection.
References
Balakrishnan R, Suresh KK (2001). “Strategies for developing core collections of safflower (Carthamus tinctorius L.) germplasm-part II. Using an information measure for obtaining a core sample with pre-determined diversity levels for several descriptors simultaneously.” Indian Journal of Plant Genetic Resources, 14(1), 32–42.
Examples
suppressPackageStartupMessages(library(EvaluateCore))
library(EvaluateCore)
# Get data from EvaluateCore
data("cassava_EC", package = "EvaluateCore")
# Data of 'Colour of unexpanded apical leaves' qualitative trait
CUAL <- as.factor(cassava_EC$CUAL)
# Raw relative frequencies
prop.adj(CUAL, method = "none")
#> Dark green Green Green purple Light green Purple
#> 0.190617577 0.001187648 0.527909739 0.028503563 0.251781473
# Square root-proportion transformed relative frequencies
prop.adj(CUAL, method = "sqrt")
#> Dark green Green Green purple Light green Purple
#> 0.23369439 0.01844636 0.38890779 0.09036836 0.26858311
# Square log-frequency transformed relative frequencies
prop.adj(CUAL, method = "log")
#> Dark green Green Green purple Light green Purple
#> 0.24903071 0.02990846 0.29298449 0.16703765 0.26103869