One class or multiclass SAM for timecourse

  • Tamra

    Tamra - 2009-11-11

    I have a question about one or multiclass SAM for timecourse arrays.  I have Affy arrays with >10k genes represented.  Experimental design is for 27 samples (9 timepoints, 3 replicates each).  When data is loaded to MeV for One Class SAM analysis, a huge number of significant genes (~4k) are identified.  This is more genes than is practical to process by clustering methods.  I wonder if we are using the correct type of SAM analysis.  Is there a better way to use SAM for timecourse analysis?  For example, would grouping samples into 9 groups of 3
    replicates each be beneficial, and help reduce the significant hits?
    Thanks for any advice.

  • Daniel Schlauch

    Daniel Schlauch - 2009-11-11

    Hi Tam,
    Most likely, you do not want to be running One Class SAM on your affy data.  One class is typically used for two-color arrays or data with a meaningful mean value.  You might try running multi-class SAM with 9 groups and see how that turns out.
    Additionally, MeV offers a new statistical method tailored specifically to time course data, BETR (Bayesian Estimation of Temporal Regulation).  It sounds like you might be interested in this module for "One-condition".  MeV will also release version 4.5 on November 13th, which will include the widely used LIMMA method- another commonly used time course analysis.


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