Hello,
   
  I have several questions about siggenes package.
   
  1) Does this method fit with small size dataset, like real time PCR data set?
  2) If there are quite a number of NA values (missing data) in the matrix, what would they affect the SAM output?
  3) After running sam, in the summary report, it says s0=0, number of permutations: 100. Does it mean there weren't any modification for t-test since s0=0? I have 11 replicates in each before and after treatment group. I did two classes paired analysis with SAM. Again, there are many missing values in the 120x22 matrix.
   
      We have two animal models with different treatment. In each model, we observed 20 genes QPCR expression levels at six time points. At each time point, we did different numbers of the replicates (5 ~ 11) because of the technical problems. We want to know which gene at what time point differentially expressed comparing with control in each model. Also, comparing two models, we want to know which gene at what time point differentially expressed. We are trying to convert these data into mini 'microarray' dataset in order to apply SAM method. 20 genes with six time points make 120 spots (or probes) in the mini array. In each animal model, we would apply two class paired analysis for treatment and control (before treatment) groups comparison. Between two models, we would apply two class unpaired analysis comparison using the ratios from each model. I am not sure whether this is proper way to apply SAM for this kind of experiment design.
   
  Thanks for your help!
   
  Yanqin

 
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