On Thu, 22 Nov 2012, maria traka (IFR) wrote: > Thanks Gordon, > It works brilliantly! I have a hard copy of a previous limma user guide > which did not contain that section. That will teach me...Sorry for > taking up your time! > > Is there a minor mistake in there? It reads block=Person when I think it > should read block=Patient (from the targets frame). Yes, thanks. Gordon > Best wishes, > Maria > > Maria Traka, PhD, MSc > Food?& Health Programme Science Manager, > Institute of Food Research, NR4 7UA, UK > Tel: +44 (0) 1603 255194 Fax: +44 (0) 1603 507723 > e-mail: maria.traka at ifr.ac.uk > > www.ifr.ac.uk www.foodandhealthnetwork.com > e-disclaimer at http://www.ifr.ac.uk/edisclaimer/ > > PLEASE support our moustaches for PROSTATE CANCER RESEARCH: > http://uk.movember.com/team/683817 > > > -----Original Message----- > From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU] > Sent: 22 November 2012 04:50 > To: maria traka (IFR) > Cc: Bioconductor mailing list > Subject: limma design (paired and factorial?) > > Dear Maria, > > If you haven't already, install the latest official release of Bioconductor. Then look at Section 8.7 "Multi-level experiments" in the limma User's Guide, which deals with experimental designs like the one you are analysing. > > Best wishes > Gordon > >> Date: Tue, 20 Nov 2012 12:39:33 +0000 >> From: "maria traka (IFR)" <maria.traka at="" ifr.ac.uk=""> >> To: "bioconductor at r-project.org" <bioconductor at="" r-project.org=""> >> Subject: [BioC] limma design (paired and factorial?) >> >> Dear list, > >> I am not sure how to create the proper design in limma for my >> experiment which I think is a factorial and paired combined. >> >> I have 9 patients that are on 3 different diets (3 patients each) and >> I have paired samples (pre and post) for each. So I have a total of 18 >> Affy arrays. >> >> I want to mainly determine the genes that are affected in each diet. >> Then I also want to get the genes that are changing in the diets at >> the 'pre' stage to get an indication of the variation in my starting >> population. So I have made a targets file that looks like this: >> targets > >> ArrayNames Person Diet Time >> 1 JALI-173_post 173 Control post >> 2 JALI-173_pre 173 Control pre >> 3 JALI-205_post 205 lowFV post >> 4 JALI-205_pre 205 lowFV pre >> 5 JALI-223_post 223 Control post >> 6 JALI-223_pre 223 Control pre >> 7 JALI-225_post 225 highFV post >> 8 JALI-225_pre 225 highFV pre >> 9 JALI-235_post 235 lowFV post >> 10 JALI-235_pre 235 lowFV pre >> 11 JALI-245_post 245 lowFV post >> 12 JALI-245_pre 245 lowFV pre >> 13 JALI-252_post 252 highFV post >> 14 JALI-252_pre 252 highFV pre >> 15 JALI-263_post 263 highFV post >> 16 JALI-263_pre 263 highFV pre >> 17 JALI-276_post 276 Control post >> 18 JALI-276_pre 276 Control pre >> >> >> then, >> >> person<-factor(targets$Person) >> >> diet<-factor(targets$Diet, levels=c("highFV","lowFV","Control")) >> >> time<-factor(targets$Time, levels=c("Pre", "Post")) >> >> So I am kind of stuck with the design and the model to use for my data >> and also how to make contrasts and get the comparisons I want. >> >> Please can you give me any help? >> Thanks in advance. >> Maria >> >> >> >> Maria Traka, PhD, MSc >> Food & Health Programme Science Manager, Institute of Food Research, >> NR4 7UA, UK >> Tel: +44 (0) 1603 255194 Fax: +44 (0) 1603 507723 >> e-mail: maria.traka at ifr.ac.uk<mailto:maria.traka at="" bbsrc.ac.uk=""> >> >> www.ifr.ac.uk www.foodandhealthnetwork.com > > ______________________________________________________________________ > The information in this email is confidential and inte...{{dropped:11}}