I am starting a new project using Affymetrix U133 2.0, and hope to seek suggestions on completing the analysis within 1 to 2 months. The objective is to identify differentially expressed genes, and to perform gene ontology analysis. Now I am at a loss given the diverse packages and algorithms to choose from. _________________________________________________________________ [[alternative HTML version deleted]]

Hi, On Oct 29, 2008, at 9:21 AM, Daren Tan wrote: > I am starting a new project using Affymetrix U133 2.0, and hope to > seek suggestions on completing the analysis within 1 to 2 months. > The objective is to identify differentially expressed genes, and to > perform gene ontology analysis. Now I am at a loss given the diverse > packages and algorithms to choose from. The affy - Primer vignette and the limma user's are as good of a place to start as any, I reckon. Although the limma user's guide has a lot to do with two-color array analysis, I'm sure it'll be generally helpful, but also Section 7.2 talks directly to dealing with affy and other "single channel designs". To get to the affy vignettes, just: R> library(affy) R> openVignette() And chose the number associated to "Primer" -- reading through all of those documents couldn't hurt though :-) To get the limma user's guide: R> library(limma) R> limmaUsersGuide() HTH, -steve -- Steve Lianoglou Graduate Student: Physiology, Biophysics and Systems Biology Weill Medical College of Cornell University http://cbio.mskcc.org/~lianos

> I am starting a new project using Affymetrix U133 2.0, and hope to > seek suggestions on completing the analysis within 1 to 2 months. > The objective is to identify differentially expressed genes, and to > perform gene ontology analysis. Now I am at a loss given the diverse > packages and algorithms to choose from. Also, for GO analysis, have a look at the GOstats package: http://bioconductor.org/packages/2.3/bioc/html/GOstats.html -steve -- Steve Lianoglou Graduate Student: Physiology, Biophysics and Systems Biology Weill Medical College of Cornell University http://cbio.mskcc.org/~lianos

Hi Daren, At the very least you will need the affy package. For differential expression there are many choices depending on the experimental design. For simple comparisons you can use things like multtest or siggenes (or even rowttests() in Biobase). For more complex comparisons you might want to use limma. For GO analysis you can use GOstats or topGO. And <shameless plug=""> you could use affycoretools to (possibly) make your life easier </shameless>. The relevant biocViews page is here: http://www.bioconductor.org/packages/release/OneChannel.html Best, Jim Daren Tan wrote: > I am starting a new project using Affymetrix U133 2.0, and hope to > seek suggestions on completing the analysis within 1 to 2 months. The > objective is to identify differentially expressed genes, and to > perform gene ontology analysis. Now I am at a loss given the diverse > packages and algorithms to choose from. > _________________________________________________________________ > > > [[alternative HTML version deleted]] > > _______________________________________________ Bioconductor mailing > list Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor Search the > archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor -- James W. MacDonald, M.S. Biostatistician Hildebrandt Lab 8220D MSRB III 1150 W. Medical Center Drive Ann Arbor MI 48109-0646 734-936-8662

29/10/2008 13:21 Daren Tan scripsit > I am starting a new project using Affymetrix U133 2.0, and hope to seek suggestions on completing the analysis within 1 to 2 months. The objective is to identify differentially expressed genes, and to perform gene ontology analysis. Now I am at a loss given the diverse packages and algorithms to choose from. Chapter 3 of this would be one place to start: http://www.amazon.com/gp/product/0387772391 Best wishes Wolfgang ------------------------------------------------------------------ Wolfgang Huber EBI/EMBL Cambridge UK http://www.ebi.ac.uk/huber

Hello, you might want to have a look at the following packages: - affy: for importing the data and preprocessing - arrayQualityMetrics: for quality assessment of the arrays - hgu133a2.db: for the annotation of the probe sets on the microarray - limma, siggenes: for finding differentially expressed genes - topGO, GOstats: find perform gene set enrichment analysis with GO This list of packages is not meant to be exhaustive, and other Bioconductor packages surely will help you with these steps just as nicely. Since your analysis seems to be pretty much standard, there is lots of documentation that can help you get started. You can find relevant chapters in the books - Bioinformatics and Computational Biology Solutions Using R and Bioconductor - Bioconductor Case Studies The vignettes of packages limma, affy, topGO etc. may also be very useful. Regards, Joern Daren Tan wrote: > I am starting a new project using Affymetrix U133 2.0, and hope to seek suggestions on completing the analysis within 1 to 2 months. The objective is to identify differentially expressed genes, and to perform gene ontology analysis. Now I am at a loss given the diverse packages and algorithms to choose from. > _________________________________________________________________ > > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Joern Toedling EMBL - European Bioinformatics Institute Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD United Kingdom Phone +44(0)1223 492566 Email toedling at ebi.ac.uk