Hi, I have a set of Affymetrix array data 3 groups (two treatment one control) of 5 individuals in each. I have analysed by fitting my model with a contrast of treatment-control, and treatment2-control to the linear model, using an eBayes correction, then listed the top genes using topTable. I have been asked to 'bootstrap' my results to 'weed-out' false positives before QPCR validation. Is this a necessary step? And if so at what stage do I use it and how do I go about applying it to my expression data to find the differentially expressed genes? My background is definitely not in statistics so any discussion or pointers would be gratefully received! Thank you Alice P Think before you print This e-mail transmission and any attachments that accompany it may contain information that is privileged, confidential or otherwise exempt from disclosure under applicable law and is intended solely for the use of the individual(s) to whom it was intended to be addressed. If you have received this e-mail by mistake, or you are not the intended recipient, any disclosure, dissemination, distribution, copying or other use or retention of this communication or its substance is prohibited. If you have received this communication in error, please immediately reply to the author via e-mail that you received this message by mistake and also permanently delete the original and all copies of this e-mail and any attachments from your computer. Thank you.

Hi Alice, I think what 'they' want is for you to estimate the null distribution by permuting the class labels for your samples. You can do this easily using the multtest package. The siggenes package will do this as well, and will also do some ad hoc shrinkage of the test denominator sort of like what limma does. Best, Jim Johnstone, Alice wrote: > Hi, > I have a set of Affymetrix array data 3 groups (two treatment one > control) of 5 individuals in each. I have analysed by fitting my model > with a contrast of treatment-control, and treatment2-control to the > linear model, using an eBayes correction, then listed the top genes > using topTable. I have been asked to 'bootstrap' my results to > 'weed-out' false positives before QPCR validation. > Is this a necessary step? And if so at what stage do I use it and how > do I go about applying it to my expression data to find the > differentially expressed genes? > My background is definitely not in statistics so any discussion or > pointers would be gratefully received! > > Thank you > > Alice > > P Think before you print > This e-mail transmission and any attachments that accompany it may contain information that is privileged, confidential or otherwise exempt from disclosure under applicable law and is intended solely for the use of the individual(s) to whom it was intended to be addressed. > If you have received this e-mail by mistake, or you are not the intended recipient, any disclosure, dissemination, distribution, copying or other use or retention of this communication or its substance is prohibited. If you have received this communication in error, please immediately reply to the author via e-mail that you received this message by mistake and also permanently delete the original and all copies of this e-mail and any attachments from your computer. Thank you. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- James W. MacDonald, MS Biostatistician UMCCC cDNA and Affymetrix Core University of Michigan 1500 E Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623

On Sep 25, 2007, at 3:48 PM, Johnstone, Alice wrote: > Hi, > I have a set of Affymetrix array data 3 groups (two treatment one > control) of 5 individuals in each. I have analysed by fitting my > model > with a contrast of treatment-control, and treatment2-control to the > linear model, using an eBayes correction, then listed the top genes > using topTable. I have been asked to 'bootstrap' my results to > 'weed-out' false positives before QPCR validation. > Is this a necessary step? And if so at what stage do I use it and how > do I go about applying it to my expression data to find the > differentially expressed genes? > My background is definitely not in statistics so any discussion or > pointers would be gratefully received! Why don't you ask the people who told you to do this: they should be in a prime position to know what they mean. > Thank you > > Alice > > P Think before you print > This e-mail transmission and any attachments that accompany it may > contain information that is privileged, confidential or otherwise > exempt from disclosure under applicable law and is intended solely > for the use of the individual(s) to whom it was intended to be > addressed. > If you have received this e-mail by mistake, or you are not the > intended recipient, any disclosure, dissemination, distribution, > copying or other use or retention of this communication or its > substance is prohibited. If you have received this communication in > error, please immediately reply to the author via e-mail that you > received this message by mistake and also permanently delete the > original and all copies of this e-mail and any attachments from > your computer. Thank you. So do you think this applies to an email list? Kasper