Ranks are used to score genes with respect to degree of agreement to a given trend or pattern, Lehmann (1974) p.294.
Usage
rank.trend(data = x, pattern = c(1:ncol(data)), har = FALSE)
Arguments
data
A data frame with one array in each column
pattern
A permutation of the integers 1:ncol(data)
har
logical parameter indicating whether or not a score based on Hardy's theorem shall be calculated.
Value
A list with the components
scorethe rank score for each gene
hardyif har = TRUE the hardy score, NULL otherwise
pvalsthe p-values for the null hypothesis of no trend
Details
The rank scores gives a higher weight to a deviation from trend in more distant obseveations than a deviation between neighbouring observations.
The p-values are calculated through a normal approximation.
References
Lehmann, E.L. (1975) Nonparametrics: Statistical Methods Based on Ranks, Holden-Day