fit.li.wong is ment to follow li and wong's paper. takes an I x J matrix containing the probe set data. Typically the i,j entry will contain the PM-MM (or PM) value for probe pair j in chip i. li.wong is ment to work in the context of the express function. so its the transponse as you have noticed. fit.li.wong takes in a matrix and returns the fitted phi's and thetas (among other things) of the li and wong model. it doesnt normalize. the "invariantset" option in the normalize function does something similar to what dChip does. hope this helps rafael On Thu, 26 Sep 2002, Tibor van Rooij wrote: > Hi! do li.wong( ) and fit.li.wong( ) have their matrix indeces reversed? > > when I use the example: > > x <- sweep(matrix(2^rnorm(600),30,20),1,seq(1,2,len=30),FUN="+") > > and I use li.wong(x,verbose=T) > > it claims it has : > > chips used= 20 , probes used= 30 > > however when I use fit.li.wong(x,verbose=T) > > it says it has: > > chips used= 30 , probes used= 20 > > Does anybody know why? What I really would like to do is give it a matrix and get a matrix with of the same dimension with the normalized values back as I can with normalize.quantiles(x) for quantile normalization. > > Has anybody succeeded in doing this? > > Tibor > _______________________________ > Tibor van Rooij > Bioinformatician > Montreal Genome Centre > McGill University, Duff Building > Tel: (514) 398-2497 > Fax: (514) 398-1838 > >