This is a naďve question. Is there some BioConductor package to estimate mixed models on Affymetrix data? I have a 2 x 2 design, treatment versus control at two labs. There are strong (lab) batch effect that can be seen by clustering the data. So far I have computed RMA (and GCRMA) values for each lab separately, normalized across arrays using limma's normalizeBetweenArrays (quantile) and generated lists of potentially differentially expressed genes via lmFit, eBayes and TopTable. I would like to estimate how much of a batch effect remains. >From my numeralogist roots, I know that a mixed model across all arrays need not give the same estimates as a linear model of the residuals from linear models derived for each lab. Any pointer on how other people handle batch effects would be most useful and most welcome. With best regards to all, Joel M. Malard, Ph.D. Scientist IV Pacific Northwest National Laboratory Tel: +509 372-6539 Fax: +509 375-2604 Battelle Boulevard, PO Box 999 Mail Stop K6-08 Richland, WA 99352 "I love the audacity of those who have everything to lose from it; the moderation of those who have nothing to gain from it." Rostand, Jean (1894-1977) [[alternative HTML version deleted]]

Dear group: I have a couple of questions. 1. I have 250 CEL files from various experimental sources. My aim is to extract gene expression values (and not the fold changes) for every gene on chromosome 17. I obtained the gene expression values in the following way: my_expr_values <-exprs(justRMA()) Is it true that I have expression values for all the probesets in my_expr_values? Or did I miss any crucial step here. Question 2: For many genes affymetrix assigned 2 or more probesets. For egfr gene there are 4 probe_sets. Now that I want expression values for 'single gene', what do I have to do to assign an expression value to a single gene. Does the program averages the experssion values for 4 probe_sets and assigns a single expression value to EGFR gene? 3 Question: How can I obtain genes on chromosome 17. library(hgu133a) my_chr_list <- as.list(hgu133aCHR) my_gene_name <- as.list(hgu133SYMBOL) How can I associate the gene_name to the probe_set (with Expression values) and chromosome number. Can any one please help me. Thank you. Srini

>>From my numeralogist roots, I know that a mixed model across all arrays >> need not give the same estimates as a linear model of the residuals from >> linear models derived for each lab. Any pointer on how other people >> handle batch effects would be most useful and most welcome. If I use linear model. I would normalize all arrays (from boht labs) together and include "batch" effect as one factor in the linear model. If only identifying differentially expressed genes between two conditions, there is a method called "rank product" can handle this situation (two lab data) directly. Hopefully this helps. Fangxin > With best regards to all, > > Joel M. Malard, Ph.D. > Scientist IV > Pacific Northwest National Laboratory > Tel: +509 372-6539 Fax: +509 375-2604 > Battelle Boulevard, PO Box 999 > Mail Stop K6-08 > Richland, WA 99352 > > "I love the audacity of those who have everything to lose from it; the > moderation of those who have nothing to gain from it." Rostand, Jean > (1894-1977) > > > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > > -- Fangxin Hong, Ph.D. Plant Biology Laboratory The Salk Institute 10010 N. Torrey Pines Rd. La Jolla, CA 92037 E-mail: fhong@salk.edu