[BioC] limma design (paired and factorial?)

[maria traka (IFR)]

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

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-----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

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