I've been applying FIRMA on the Gardina et.al (http://
www.biomedcentral.com/1471-2164/7/325) Human Exon Array dataset which
has been summarized based on mappings from the BrainArray CustomCDFs
(in particular ENSE13).  Taking the list of genes which have been
validated through PCR, I found the corresponding probesets on the
customCDF which interrogate the differentially spliced exons.  When I
plot an ROC curve for the positive and negative probesets according to
the paper using the FIRMA scores, the ROC curve shows poor results by
FIRMA (auc =0.4949367)

When I do the analysis using the official CDF from affymetrix sticking
to the positive and negatives probesets listed in the FIRMA paper  by
Purdom et. al (http://bioinformatics.oxfordjournals.org/content/
24/15/1707.abstract), the ROC curve does very well (auc=0.89)

I find this puzzling considering that the customCDF from the
Brainarray group is considered to be more accurate since they filter
out all the problematic probesets (eg. multi-mapping).  One would
expects the FIRMA scores to be better when using these re-annotated

I am thinking it might be because the probesets might contain less
probes in them than before and thus when fitting RMA and calculating
the residuals from the fitting, the residuals might be skewed or less
accurate due to lesser probes contributing to the FIRMA score?  Does
anyone have any ideas as to why FIRMA does so poorly with the



When reporting problems on aroma.affymetrix, make sure 1) to run the latest 
version of the package, 2) to report the output of sessionInfo() and 
traceback(), and 3) to post a complete code example.

You received this message because you are subscribed to the Google Groups 
"aroma.affymetrix" group with website http://www.aroma-project.org/.
To post to this group, send email to aroma-affymetrix@googlegroups.com
To unsubscribe and other options, go to http://www.aroma-project.org/forum/

Reply via email to