Hello, I have an Affymetrix time series experiment, and am following the estrogen example of the limma User's Guide to get started. I am feeling rather unconfident, and would like to know whether I am performing the best analysis. If someone has time to take a look and offer advice, I would be very appreciative. The study has 7 time points, 2 genotypes, 2 replicates of each (28 arrays). Of interest are genes that are differentially expressed between genotypes across all time states but the first (time0). I have run the data through rma (worked beautifully!) and set up the design with 14 treatments: genotype1_time1, genotype1_time2.... genotype2_time1, genotype2_time2.... And set up 6 contrasts: genotype1_time2 - genotype2_time2 genotype1_time3 - gentotype2_time3 ... My questions follow the code below. The code: treatment.vector<-c(rep(1,2),rep(2,2),rep(3,2), rep(4,2), rep(5,2), rep(6,2), rep(7,2), rep(8,2),rep(9,2),rep(10,2),rep(11,2),rep(12,2),rep(13,2),rep(14,2)) treatments<-factor(treatment.vector,labels=exp.labels) design<-model.matrix(~-1+treatments) fit <- lmFit(Mrma, design) contrast.matrix<-makeContrasts(KO.15min-WT.15min, KO.30min-WT.30min, KO.90min-WT.90min, KO.3hr-WT.3hr, KO.6hr-WT.6hr, KO.24hr-WT.24hr,levels=design) fit2 <- contrasts.fit(fit, contrast.matrix) fit3 <- eBayes(fit2) clas <- classifyTestsF(fit3,fstat.only=FALSE) FStats<-FStat(fit3) G1<-topTable(fit3,coef=1,number=1000,adjust="fdr",sort.by="P") ##15min G1<-topTable(fit3,coef=2,number=1000,adjust="fdr",sort.by="P") ##30min The Questions: 1) Is this an ok model to use, or is it better to include the intercept? 2) How would I report either linear model via an equation? 3) Should one perform a multiple testing correction on the FStat p-values? 4) Should the genes supplied by the signficant FStats(fit3) have all non-zero values in the 6 contrasts? (they do not) 5) If I would like to look at all genes that are differentially expressed between time points 2 and 3 across genotypes, is it best to simply extract these from the significant FStats group that have nonzero values in contrasts 1 and 2, or choose the intersection between G1 and G2? argh - I have so much to learn. Thanks, folks, for helping. Karen Schlauch

> The Questions: > 1) Is this an ok model to use, or is it better to include the intercept? doesn't matter whether you include intercept or not, they are equivalent models > 2) How would I report either linear model via an equation? gene expression at time t under condition i=true gene expression at time t under condition i + noise > 3) Should one perform a multiple testing correction on the FStat p-values? If yo want to control overall significance of your identification, you should. > 4) Should the genes supplied by the signficant FStats(fit3) have all > non-zero > values in the 6 contrasts? (they do not) I am not sure about this, but I think the FState still test each value separately. You can select genes who have non-zero values in the 6 contrasts manually. > 5) If I would like to look at all genes that are differentially expressed > between time points 2 and 3 across genotypes, is it best to simply > extract these from the significant FStats group that have nonzero values > in contrasts 1 and 2, or choose the intersection between G1 and G2? It depends on your data and what you want. G1 and G2 give you top 1000 genes no matter they are significant or not. Fstats give you all significant genes which maybe less or more than 1000. Maybe you can start with Fstat result as it has significnat genes. Fangxin -- Fangxin Hong, Ph.D. Plant Biology Laboratory The Salk Institute 10010 N. Torrey Pines Rd. La Jolla, CA 92037 E-mail: fhong@salk.edu

Hi, The Bioconductor packages (e.g., affy, LPE) are not being properly installed by the new 2.0 version of R. JMW [[alternative HTML version deleted]]

On Fri, Oct 08, 2004 at 12:53:38AM -0400, Wolosin, Jose wrote: > Hi, The Bioconductor packages (e.g., affy, LPE) are not being properly installed by the new 2.0 version of R. JMW > Could you please provide 1) a description of the platform and 2) a reproducible error message as it is virtually impossible for anyone to help you given this information, nor is it entirely correct since I at least do it on a daily basis. Robert > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor -- +--------------------------------------------------------------------- ------+ | Robert Gentleman phone : (617) 632-5250 | | Associate Professor fax: (617) 632-2444 | | Department of Biostatistics office: M1B20 | | Harvard School of Public Health email: rgentlem@jimmy.harvard.edu | +--------------------------------------------------------------------- ------+

Hi Folks, Thanks, Fangxin, for your replies. I still have a few questions on my linear model for the following experiment. If someone could help, I'd be grateful. This is an an Affymetrix time series experiment, 7 time points, 2 genotypes, 2 replicates of each (28 arrays). Of interest are genes that are differentially expressed between genotypes across all but the first time state. The design I set up with 14 treatments and 6 contrasts: genotype1_time1, genotype1_time2.... genotype2_time1, genotype2_time2.... genotype1_time2 - genotype2_time2 genotype1_time3 - gentotype2_time3 ... The code: treatment.vector<-c(rep(1,2),rep(2,2),rep(3,2), rep(4,2), rep(5,2), rep(6,2), rep(7,2), rep(8,2),rep(9,2),rep(10,2),rep(11,2),rep(12,2),rep(13,2),rep(14,2)) treatments<-factor(treatment.vector,labels=exp.labels) design<-model.matrix(~-1+treatments) fit <- lmFit(Mrma, design) contrast.matrix<-makeContrasts(KO.15min-WT.15min, KO.30min-WT.30min, KO.90min-WT.90min, KO.3hr-WT.3hr, KO.6hr-WT.6hr, KO.24hr- WT.24hr,levels=design) fit2 <- contrasts.fit(fit, contrast.matrix) fit3 <- eBayes(fit2) clas <- classifyTestsF(fit3,fstat.only=FALSE) FStats<-FStat(fit3) The Questions: 1) Is this an acceptable model to use? 2) How would I report the model via an equation? Even using contrasts, (2 main effects) will the model be written as Y=xij + e 3) Should significant FStats be significant in 1 or more contrasts, but not necessarily in all six? Thank you for any help, Karen

I am trying to update bioc packages and I got the following error: getBioC(develOK=TRUE,libName='annotation') Running getBioC version 1.2.65.... If you encounter problems, first make sure that you are running the latest version of getBioC() which can be found at: www.bioconductor.org/getBioC.R Please direct any concerns or questions to bioconductor@stat.math.ethz.ch. [1] "Test:" [1] "affy" "cdna" "default" "exprs" "prog" [6] "graph" "widgets" "database" "design" "annotation" [11] "analyses" "externalData" "proteomics" "arrayCGH" Error in grep("[[:alpha:]]", vers) : couldn't find function "getRversion" platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status Under development (unstable) major 2 minor 0.0 year 2004 month 08 day 13 language R Thanks in advance.. -- Mayte Suarez Farinas The Rockefeller University 1230 York Avenue, Box 212 New York, NY 10021 phone: 1-212-327-8186 fax: 1-212-327-7422

On Mon, Oct 18, 2004 at 07:18:00PM -0400, Mayte Suarez-Farinas wrote: > > I am trying to update bioc packages and I got the following error: > > getBioC(develOK=TRUE,libName='annotation') > Running getBioC version 1.2.65.... > If you encounter problems, first make sure that > you are running the latest version of getBioC() > which can be found at: www.bioconductor.org/getBioC.R > > Please direct any concerns or questions to bioconductor@stat.math.ethz.ch. > > [1] "Test:" > [1] "affy" "cdna" "default" "exprs" "prog" > [6] "graph" "widgets" "database" "design" > "annotation" > [11] "analyses" "externalData" "proteomics" "arrayCGH" > Error in grep("[[:alpha:]]", vers) : couldn't find function "getRversion" Hi, getRversion should be a function supplied by R, try find("getRversion") for most of us we should get answer like: [1] "package:base" if you do not then you will probably need to repair, or replace, your R installation. Robert > > > platform i686-pc-linux-gnu > arch i686 > os linux-gnu > system i686, linux-gnu > status Under development (unstable) > major 2 > minor 0.0 > year 2004 > month 08 > day 13 > language R > > Thanks in advance.. > -- > Mayte Suarez Farinas > The Rockefeller University > 1230 York Avenue, Box 212 > New York, NY 10021 > phone: 1-212-327-8186 > fax: 1-212-327-7422 > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor -- +--------------------------------------------------------------------- ------+ | Robert Gentleman phone : (617) 632-5250 | | Associate Professor fax: (617) 632-2444 | | Department of Biostatistics office: M1B20 | | Harvard School of Public Health email: rgentlem@jimmy.harvard.edu | +--------------------------------------------------------------------- ------+

hai, Iam an Masters student from University of North carolina and I would like to do an individual project in bioinofrmatics. Please tell me how can i take a help from bioconductor. Thanking you, Krishna.