orderFeatures {hddplot} | R Documentation |
For each row of data
, an F or (potentially) other
statistic is calculated, using the function FUN
, that measures
the extent to which this variable separates the data into groups. This
statistic is then used to order the rows.
orderFeatures(x, cl, subset = NULL, FUN = aovFbyrow, values = FALSE)
x |
Matrix; rows are features, and columns are observations ('samples') |
cl |
Factor that classifies columns into groups |
subset |
allows specification of a subset of the columns of data |
FUN |
specifies the function used to measure separation between groups |
values |
if TRUE , F-values as well as the ordering are returned |
Either (values=FALSE
) a vector that orders the rows,
or (values=TRUE
)
ord |
a vector that orders the rows |
stat |
ordered values of the statistic |
John Maindonald
mat <- matrix(rnorm(1000), ncol=20) cl <- factor(rep(1:3, c(7,9,4))) ord <- orderFeatures(mat, cl) ## The function is currently defined as function(x, cl, subset=NULL, FUN=aovFbyrow, values=FALSE){ if(dim(x)[2]!=length(cl))stop(paste("Dimension 2 of x is", dim(x)[2], "differs from the length of cl (=", length(cl))) ## Ensure that cl is a factor & has no redundant levels if(is.null(subset)) cl <- factor(cl) else cl <- factor(cl[subset]) if(is.null(subset)) stat <- FUN(x, cl) else stat <- FUN(x[, subset], cl) ord <- order(-abs(stat)) if(!values)ord else(list(ord=ord, stat=stat[ord])) }