limma design (paired and factorial?)
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@maria-traka-ifr-5544
Last seen 9.6 years ago
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@ifr.ac.uk<mailto:maria.traka@bbsrc.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 [[alternative HTML version deleted]]
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@gordon-smyth
Last seen 7 hours ago
WEHI, Melbourne, Australia
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 intend...{{dropped:4}}
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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). 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@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 intend...{{dropped:6}}
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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}}
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