Is there a technique in Bioconductor for selecting genes associated with a linear response such as chemotherapy response (IC50), while accounting for false discovery rates/multiple testing? I could not find an explicit procedure with this intent. Neil Hayes

david neil hayes wrote: > Is there a technique in Bioconductor for selecting genes associated with > a linear response such as chemotherapy response (IC50), while accounting > for false discovery rates/multiple testing? I could not find an > explicit procedure with this intent. I believe you can use the limma package for this sort of analysis. The paradigm is to use lmFit() to fit an ANOVA, but as this is just a wrapper to lm.fit(), I don't see any reason offhand that would preclude using lmFit() for a continuous response. Since the paradigm is to use lmFit() for ANOVA, most of the documentation has the following code: design <- model.matrix(~ -1 + factor(c(1,1,1,2,2,2))) Which will fit an ANOVA with two factor levels and no intercept. To fit a continuous variable you would remove the factor() statement and instead use the amounts of chemo drug you used. I would also recommend fitting an intercept unless you have a reason to believe the regression line should go through (0, 0). design <- model.matrix(~ c(0.1, 0.5, 1.0, 1.5, 2.0)) where 0.1, ... 2.0 are the concentrations of your drug. Best, Jim > > Neil Hayes > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor -- James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623