[BioC] Large # of significant genes with SAM

[Sean Davis]

On May 10, 2005, at 11:35 AM, Joern Toedling wrote:

> Hi Vincent,
>
> I imagine such large numbers of differentially expressed genes could 
> arise for various reasons.
> One issue could be that there are large technical or experimental 
> differences between your tumour and control samples due to scanner 
> settings or hybridisation protocols etc. I would check if after 
> normalisation such large differences between the groups are obvious by 
> using boxplots, Scatter-Plots etc. (many examples for such control 
> procedures can be found on the Bioconductor website , especially on 
> the pages containing material for courses and workshops). If so, you 
> might think about other methods for normalisation or combining the two 
> groups data in another way, if they happen to be too different.
> Another reason for large differences could be that there might really 
> be huge biological differences between the two groups. For instance, 
> when analyzing T- versus B-lymphocytes, one usually observes large 
> percentages > 20% of differentially expressed genes, since in that 
> case we were comparing very different cell types with each other. 
> However, I would not expect such striking differences between a tumour 
> and the related physiological tissue.

Vincent,

Actually, having a large proportion of differentially-expressed genes 
between tumor and normal is certainly possible.  You got the same 
results with two different data sets if I read your original post 
correctly, so go back to check quality of data, statistical biases, 
etc., but it seems quite possible that your results are correct.  You 
will, of course, have to think about validation strategies, but....

Sean