Hi All, I am using the siggenes package for SAM analysis. I have tried out the package with golub data from multtest package. But I cant understand how to pass my own expression data to the package. Can anyone plz help ASAP? Thanks and Regards Madhurima.

On 10/26/05 3:45 AM, "madhurima bhattacharjee" <madhurima_b at="" persistent.co.in=""> wrote: > Hi All, > > I am using the siggenes package for SAM analysis. > I have tried out the package with golub data from multtest package. > But I cant understand how to pass my own expression data to the package. > Can anyone plz help ASAP? One way is to make a matrix from your data where rows represent genes and columns represent samples. Then, you need to make your class vector. Some examples are in the package vignette. If you call your matrix "mymat" and your class vector "my.cl", then you can simply replace "golub" with "mymat" and "golub.cl" with "my.cl" and run the examples as given. I think the gene names are optional, but you can make your own vector of gene names to pass to SAM, also, if you like. I'm not sure what the particular hang-up is for you, so you will have to send us more details and code of what you have tried and how it has failed for anyone to help more. Sean

On 10/26/05 6:53 AM, "madhurima bhattacharjee" <madhurima_b at="" persistent.co.in=""> wrote: > Hello Sean, > Thanks for the response. > Given below is the part of the code and the error that I am getting: > >> sam.out <- sam(madhu1,my.cl) > Error in fudge2(r, s, alpha = s.alpha, include.zero = include.zero) : > For the computation of the fugde factor, > there should be at least 25 genes with differing standard deviations. > > Here madhu is the matrix and my.cl is the class vector. > What is the problem with the data? > Could you please tell me how to solve this. I don't use siggenes often enough to know if this message means more than it says, so I can't be sure. But, what does madhu look like? How did you make that matrix? The error message is implying that there are very few genes that show any variation. Perhaps someone who uses siggenes more often can be more specific. Sean

Hi Madhurima, to your first email: data in sam(...) must not necessarily be a matrix or data frame. It can also be an exprSet object. If data is specified by an exprSet object and if you have already specified the class labels in the corresponding phenoData object, you can also specify cl by the name of column of the phenoData matrix that contains the class labels. to the fudge factor problem: This problem usually occurs when you have a too small number of genes (please recall that you actually should have a few hundred genes when applying SAM). In the computation of the fudge factor as described in the Tusher paper, the standard deviations are divided into intervals (usually, 101 intervals, fudge2 also allows a much smaller number of intervals, namely down to 5, where in each of these intervals have to be 5 values) to compute the fudge factor. If there are less than 25 genes or more precisely less than 25 genes with differing standard deviations, fudge2 stops and returns the error you have got. You can solve this problem by either using more genes (e.g., don't filter before SAM) or by setting s.alpha in sam(...) to a reasonable value. Tibshirani, e.g., uses in the Excel implementation s.alpha=0.5. Best, Holger > --- Urspr?ngliche Nachricht --- > Von: Sean Davis <sdavis2 at="" mail.nih.gov=""> > An: madhurima bhattacharjee <madhurima_b at="" persistent.co.in=""> > Kopie: Bioconductor <bioconductor at="" stat.math.ethz.ch=""> > Betreff: Re: [BioC] passing my data to siggenes package > Datum: Wed, 26 Oct 2005 07:43:58 -0400 > > On 10/26/05 6:53 AM, "madhurima bhattacharjee" > <madhurima_b at="" persistent.co.in=""> wrote: > > > Hello Sean, > > Thanks for the response. > > Given below is the part of the code and the error that I am getting: > > > >> sam.out <- sam(madhu1,my.cl) > > Error in fudge2(r, s, alpha = s.alpha, include.zero = include.zero) : > > For the computation of the fugde factor, > > there should be at least 25 genes with differing standard deviations. > > > > Here madhu is the matrix and my.cl is the class vector. > > What is the problem with the data? > > Could you please tell me how to solve this. > > I don't use siggenes often enough to know if this message means more than > it > says, so I can't be sure. But, what does madhu look like? How did you > make > that matrix? The error message is implying that there are very few genes > that show any variation. Perhaps someone who uses siggenes more often can > be more specific. > > Sean > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > --