hi, has anyone experience how good rma performs on affymetrix experiments where the data from different cell lines are compared against each other? i have 4 chips, one with cell line 1 with treatment, one with cell line 1 without treatment, one with cell line 2 with treatment and one with cell line 2 without treatment. the question is, should i normalize all them together using rma, or should i normalize cell line 1 (+/- treatment) and cell line 2 (+/- treatment) separatly. As i have no replicates, i am hoping, as the cell lines are not that different, that the model parameters are better fitted into the data. thanks, jo

hi, I was looking at the Bayesian method of selecting genes. I used the commands library(limma) fit <- lmFit(x,design=y)#x is the datafile #y is the template eb2<- eBayes(fit) topTable(eb2,coef=,number=15,adjust="fdr") I found that that the two groups could be defined by the template in two ways either (0,0,0,0,1,1,1,1) or (-1,-1,-1,-1,1,1,1,1) (I tryed other templates and all give one of the two gene lists) Both methods return a gene list, so my questions are; 1. Are both methods correct? 2. If so why do they return different gene lists and what is the significance of this? thanks, Ian

We commonly compare multiple cell lines in a single experiment using rma. The goal is different (which genes are differentially expressed in the different cell lines). However, I have never seen anything that indicated that normalizing different cell lines together was a bad thing. 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 >>> "Dipl.-Ing. Johannes Rainer" <johannes.rainer@tugraz.at> 07/16/04 05:01AM >>> hi, has anyone experience how good rma performs on affymetrix experiments where the data from different cell lines are compared against each other? i have 4 chips, one with cell line 1 with treatment, one with cell line 1 without treatment, one with cell line 2 with treatment and one with cell line 2 without treatment. the question is, should i normalize all them together using rma, or should i normalize cell line 1 (+/- treatment) and cell line 2 (+/- treatment) separatly. As i have no replicates, i am hoping, as the cell lines are not that different, that the model parameters are better fitted into the data. thanks, jo _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor