Hi Klaus-Peter Florian's comments are correct. The aim of NPI normalisation is to scale your assay results such that the dynamic range of the assay be mapped to [0,1], i.e. 0 correspond to one extreme and 1 to the other, and the extremes are taken from the values of the positive and negative controls. This assumes that the positive and negative controls are chosen accordingly. Please let us know whether you have further questions, or if you have suggestions how to make the documentation more clear to avoid such misunderstandings. Best wishes Wolfgang ------------------------------------------------------------------ Wolfgang Huber EBI/EMBL Cambridge UK http://www.ebi.ac.uk/huber Florian Hahne a ?crit 10/05/2008 01:27: > Hi Klaus-Peter, > taking a look at the source code for function NPI it seems that it > doesn't support activator and inhibitor controls, which I guess makes > sense. NPI is defined as > > (my_pos - x_i) / (my_pos - my_neg) > > and assuming that the set of positive activator controls has positive > values and the inhibitor controls have negative values, trying to > combine them doesn't give you anything useful. You could use either the > inhibitor or the activator controls like this: > > x <- normalizePlates(x, normalizationMethod="NPI",negControls=negCtr, > posControls="(?i)^Mock$",transform=log) > > Alternatively, you could treat your inhibitor controls as "negative" > controls, since all you want to archive with the normalization it to map > your values into a range that is specified by any of the controls you > are using. Technically, this wouldn't be a "normalized percent > inhibition", but then again inhibition is not what you are looking for > exclusively in a two way assay... > > Hope that helps, maybe Wolfgang or Greg have something to add to this. > Florian > > > Klaus-Peter Pleissner wrote: >> Dear all, >> >> using cellHTS (not cellHTS2) we want to perform a "NPI- normalization" >> with positive and negative control wells. >> >> According twoway. pdf vignette we define control wells as : >> >> posCtr <- list(act= "(?i)^Mock$", inh = "(?i)^NP$") >> negCtr <- "(?i)^Allstars$" >> >> and normalize by >> >> x <- normalizePlates(x, normalizationMethod="NPI",negControls=negCtr, >> posControls=posCtr,transform=log) >> >> >> >> We get an error: >> >> Error in NPI(x, posControls, negControls) : >> 'posControls' should be a vector of regular expressions with length 1 >> >> Enter a frame number, or 0 to exit 1: normalizePlates(x, >> normalizationMethod = "NPI", negControls = negCtr, posCo >> 2: switch(normalizationMethod, mean = scaleByPlateMean(x), median = >> scaleByPla >> 3: NPI(x, posControls, negControls) >> >> >> >> If we are using a negative normalization method ( as descibed in the >> vignette) >> x <- >> normalizePlates(x,normalizationMethod="negatives",negControls=negCtr, >> posControls=posCtr,transform=log) >> >> this error doesn't occur. >> >> >> What is wrong in the definition of positive control wells ? >> Thanks is advance for help. >> >> Klaus-Peter >