[BioC] SAM vs LIMMA vs EBAM

[Naomi Altman]

I have not tried EBAM, but I did do this experiment with SAM and LIMMA on a 
data set I simulated from an actual data set.

On these data, the SAM statistic and LIMMA F-test gave almost identical 
ordering of the genes.  However, the FDR adjustment was too stringent for 
SAM (i.e. the true FDR was lower than SAM's estimate) and was too liberal 
for LIMMA.

This was not a big study.  I took my gene means and variances from an 
actual study, and then added either normal or t-4 errors and a couple of 
levels of differential expression.

The sample sizes I used were very small - 2 or 4 replicates with 22000 
genes.  Results were much, much, much better with 4 replicates than with 2.

--Naomi

At 08:48 PM 3/28/2005, Wu, Xiwei wrote:
>Hi, BioC Members,
>
>I have a general question on identifying DE genes. Since there are many ways
>to do this, I am wondering whether people has compared methods such as SAM,
>EBAM, and LIMMA by applying them to the same dataset. Of course, they have
>different assumptions and different models, but should they always give
>similar results (assuming the parameter settings are optimized to get
>similar number of DE genes)? Is it better to get a common list of genes
>using three different methods? Do I have more confidence on this common list
>of genes than using a single method?
>
>Xiwei
>
>
>"EMF <COH.org>" made the following annotations.
>------------------------------------------------------------------------------
>SECURITY/CONFIDENTIALITY WARNING:  This message and any atta...{{dropped}}
>
>_______________________________________________
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch
>https://stat.ethz.ch/mailman/listinfo/bioconductor

Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111