[BioC] GCRMA Fold Change

[Sean Davis]

On 5/2/06 12:42 PM, "Jenny Drnevich" <drnevich at uiuc.edu> wrote:

> Hi Christine,
> 
> Instead on filtering on the expression values from GCRMA, I would suggest
> to use Affymetrix's Present/Marginal/Absent calls. You can get these with
> the mas5calls() function in the affy library. I use a very conservative
> filter, and only throw out genes that are "absent" on all arrays. I would
> suggest that you do this filtering before the statistical analysis for two
> reasons: 1) the error variances of the filtered genes are affecting your
> Bayesian statistics and 2) removing the genes will decrease the multiple
> test correction penalty.
> 
> However, even after filtering out these genes, you may still have many
> genes with low fold-changes that are "significant". One can argue all day
> long on whether these low fold changers are "biologically" significant or
> not, but if you prefer to follow up first on genes with higher fold
> changes, then by all means pick these out of your significant gene list.
> Just make sure to document everything clearly!

Just to point out one detail--if you filter too stringently (which Jenny is
careful not to do), you will potentially lose some of the most interesting
genes, namely those that are expressed in one group and not in another, so
there is potentially a fine line between too much filtering and not enough.

Sean