This function links the classification method to the procedures to
find the seed genes and the signatures.
If necessary this function can be rewritten in order to use a different classification method.
Actually the classification method linked is the partitioning around medoids (see pam() function for details)
Usage
classify(ddata)
Arguments
ddata
can be either a list of real values (gene expression levels) or a data-matrix where the rows are the samples and the columns are the genes.
Details
The function provides two clusters.
Value
If ddata is a list of real values (1 gene expression levels) the function calls an unbiased version of pam (see pamUnbiased() function for details). In this case two elements are returned
clusters
list of 1-2 indicators of the two clusters.
missing
list of T-F logical values where T labels the values set to missing by pamUnbiased().
If ddata is a real matrix (more than 1 expression levels) the function calls pam() and returns an object of pam class with an additional slot