Hi, I recently perform SAM using the siggenes package. I'm doing SAM on untreated vs untreated cultured for 1 hour sample. I have 16 replicates and am doing the paired two-class SAM. Ideally, there should be no significant genes but SAM in R gave me a lot of significant genes (~6000 genes with ~0% FDR). I counted the number of 2 fold genes and they are less than 100. Are there any parameters that I missed and need to adjust b/c this result seems incorrect. Here's my input and output: > sam.UT60<-sam(RG.UT60, x=c(1:16),y=c(17:32),paired=TRUE,B=200,na.rm=TRUE) Warning: There are 7958 genes with at least one missing value. s0 = 0 SAM Analysis for a set of delta: delta p0 false called FDR 1 0.2 0.245 10801.0 13948 0.189 2 0.4 0.245 8877.0 13385 0.162 3 0.6 0.245 6079.5 12508 0.119 4 0.8 0.245 3797.0 11577 0.080 5 1.0 0.245 1704.0 9837 0.042 6 1.2 0.245 812.0 8630 0.023 7 1.4 0.245 391.0 7671 0.012 8 1.6 0.245 182.5 6846 0.007 9 1.8 0.245 85.0 6091 0.003 10 2.0 0.245 39.0 5312 0.002 Warning messages: 1: multi-argument returns are deprecated in: return(r, s, r.perm, s.perm, Z, mat.samp, var.0.genes, NA.genes) 2: multi-argument returns are deprecated in: return(alpha.hat, s.zero, cv, cv.zero) 3: multi-argument returns are deprecated in: return(p0, spline.out, vec.p0) 4: multi-argument returns are deprecated in: return(tab.fdr, mat.fdr, p0) 5: multi-argument returns are deprecated in: return(d, d.sort, s, d.bar, d.perm, mat.samp, s0, FDR, p0, fdr.ngenes, BTW, why am I getting these warning messages? THANKS! Anna

First, you have (if I did my math correctly) 2^16 combinations that you could do, but you only did 200. This will make the null distribution pretty granular, so you might want to consider increasing B to something like 1000 or so. Realistically you *should* do more than 1000, but you will run into time issues pretty quickly (oddly enough siggenes was much faster in R-1.6.1 and appeared to slow down appreciably around R-1.7.1 or so. Why this is, I don't know). Note that most of the 'significant' genes you are picking up may not actually be significant in the biological sense. Then again, maybe they are. One problem (as I see it) with microarray data analysis is that we are making a strong assumption that gene expression is more or less directly related to phenotype. However, I think some genes probably get a lot done with very little change in expression whereas other genes may require a huge change in expression to effect a moderate change in phenotype. All this aside, many people require an additional fold change constraint for the genes they list as being significant. This will make most if not all of your 'significant' genes go away. As for the warning messages, these indicate that you are using an old version of siggenes that is not quite compatible with the current version of R. I would highly recommend that you upgrade to the current release version of BioC. HTH, Jim 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 >>> "Anna Cao" <yunie@caltech.edu> 12/22/03 8:02 PM >>> Hi, I recently perform SAM using the siggenes package. I'm doing SAM on untreated vs untreated cultured for 1 hour sample. I have 16 replicates and am doing the paired two-class SAM. Ideally, there should be no significant genes but SAM in R gave me a lot of significant genes (~6000 genes with ~0% FDR). I counted the number of 2 fold genes and they are less than 100. Are there any parameters that I missed and need to adjust b/c this result seems incorrect. Here's my input and output: > sam.UT60<-sam(RG.UT60, x=c(1:16),y=c(17:32),paired=TRUE,B=200,na.rm=TRUE) Warning: There are 7958 genes with at least one missing value. s0 = 0 SAM Analysis for a set of delta: delta p0 false called FDR 1 0.2 0.245 10801.0 13948 0.189 2 0.4 0.245 8877.0 13385 0.162 3 0.6 0.245 6079.5 12508 0.119 4 0.8 0.245 3797.0 11577 0.080 5 1.0 0.245 1704.0 9837 0.042 6 1.2 0.245 812.0 8630 0.023 7 1.4 0.245 391.0 7671 0.012 8 1.6 0.245 182.5 6846 0.007 9 1.8 0.245 85.0 6091 0.003 10 2.0 0.245 39.0 5312 0.002 Warning messages: 1: multi-argument returns are deprecated in: return(r, s, r.perm, s.perm, Z, mat.samp, var.0.genes, NA.genes) 2: multi-argument returns are deprecated in: return(alpha.hat, s.zero, cv, cv.zero) 3: multi-argument returns are deprecated in: return(p0, spline.out, vec.p0) 4: multi-argument returns are deprecated in: return(tab.fdr, mat.fdr, p0) 5: multi-argument returns are deprecated in: return(d, d.sort, s, d.bar, d.perm, mat.samp, s0, FDR, p0, fdr.ngenes, BTW, why am I getting these warning messages? THANKS! Anna _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor