[BioC] Limma-Contrasts-Question

[Biju Joseph]

Thanks Jenny, Your suggestion answers my question.
(i.e)

I make the following Contrasts as you suggest
1. A1-A2
2. B1-B2
3. (A1-A2)-(B1-B2)

And then the genes that are significant in contrasts 1 and 2 but not in
contrast 3 would be considered as those that have a significant response in
A and B. This is perfect and answers my question as well.

But what is still not clear to me is what happens when I use the contrast

(A1+B1)/2 - (A2+B2)/2.

Why do I get a much larger list of genes called as significantly DE when I
use this contrast compared to the method "significant in contrast 1 and 2
but not in contrast 3".

Best 
Biju

Institut für Hygiene und Mikrobiologie
Universität Würzburg
Josef-Schneider-Str. 2, Gebäude E1
97080 Würzburg
Email: bjoseph at hygiene.uni-wuerzburg.de
Tel.:    0931 201 46708
Fax:    0931 201 46445

-----Ursprüngliche Nachricht-----
Von: Jenny Drnevich [mailto:drnevich at illinois.edu] 
Gesendet: Dienstag, 16. März 2010 15:04
An: Biju Joseph; Gordon K Smyth
Cc: Bioconductor mailing list
Betreff: Re: [BioC] Limma-Contrasts-Question

Hi Biju,

One thing to consider is that the question you're asking - "which 
genes have the SAME response in A and B?" is not what a statistical 
test is designed to measure. Instead, the null hypothesis is that the 
responses are the same, and only if there is enough evidence of a 
different between the responses will the statistical test become 
significant. One possibility would be to do the 3 following contrasts:

1) A1-A2
2) B1-B2
3) (A1-A2) - (B1-B2)

The third one tests whether the response in A is the same as the 
response in B. You could do a Venn Diagram on these three contrasts, 
and a those genes that are significant in 1) and 2) but not 
significant in 3) could be considered genes that have the a 
significant response in A and the "same" (i.e., not significantly 
different) significant response in B.

Note that genes could be significant for 3), even if they change in 
the same direction, if they change by differing amounts (2-fold up 
versus 20-fold up). Whether you want to call this the "same" response 
depends on your research questions...

HTH,
Jenny

At 02:17 AM 3/15/2010, Biju Joseph wrote:
>Thanks Gordon for your answer.
>
>In my question, I was referring to the DE expressed genes in the same
>direction.
>
>What I am actually unclear about is the following.
>
>Lets say, I generate topTables for
>1. A1-A2
>2. B1-B2
>
>Now using these 2 individual tables, I could pull out the genes common
>in either direction using lets say Access.
>
>Is this method valid and safe?
>How comparable should this manually generated common response between
>strains A and B in conditions 1 and 2 be comparable to the topTable
>generated using (A1+B1)/2 - (A2+B2)/2. Of course I think that these 2
>methods should generate more or less the same results at least with
>respect to numbers of DE genes.
>
>What FC is better to report for the common response? One from using
>the (A1+B1)/2 - (A2+B2)/2 contrast or the FC from the individual
>topTables.
>
>Best
>Biju
>
>
>Quoting Gordon K Smyth <smyth at wehi.EDU.AU>:
>
>>Dear Biju,
>>
>>Using the contrast (A1+B1)/2 - (A2+B2)/2 will find genes which
>>response in the same direction, and perhaps by about the same fold
>>change, in both A and B.
>>
>>Doing separate tests for A1-A2 and B1-B2, does not require genes to
>>be changing in the same direction in A and B.
>>
>>Best wishes
>>Gordon
>>
>>>Date: Thu, 11 Mar 2010 14:49:35 +0100
>>>From: "Biju Joseph" <bjoseph at hygiene.uni-wuerzburg.de>
>>>To: <bioconductor at stat.math.ethz.ch>
>>>Subject: [BioC] Limma-Contrasts-Question
>>>Message-ID: <000001cac121$b0cbd3b0$12637b10$@uni-wuerzburg.de>
>>>Content-Type: text/plain;       charset="iso-8859-1"
>>>
>>>Dear all
>>>
>>>Sorry if this is a trivial question,
>>>My experiment design is the following
>>>2 strains (A & B) subjected to 4 conditions each (1,2,3,4) compared using
a
>>>common reference design.
>>>We are interested in various contrasts between the 8 samples.
>>>Using limma - I was able to generate topTables for the required contrasts
>>>eg:
>>>A1-B1, A2-B2, A3-B3, A4-B4
>>>A1-A2, A2-A3, B1-B2, B2-B3 and so on
>>>
>>>A comparison for example the topTable A1-A2 and B1-B2, would represent
the
>>>common response in A and B from condition 1 and condition 2.
>>>
>>>Using this manual comparison of the 2 topTables, I saw that around 400
genes
>>>are commonly differentially regulated in strain A and strain B in the
>>>conditions 1 and 2.
>>>
>>>Now when I include the following contrast in my model in limma
>>>
>>>(A1+B1)/2 - (A2+B2)/2 which in my understanding also generates the common
>>>response between condition 1 and 2 in the 2 strains A and B.
>>>
>>>The topTable generated using this contrast shows only 10 genes to be
>>>commonly differentially regulated between condition 1 and 2.
>>>
>>>Would be great if someone could explain this discrepancy to me and about
>>>which method is safer to compare(comparison of the 2 individual toptables
or
>>>the toptable generated using make.contrasts).
>>>
>>>Best
>>>Biju
>>______________________________________________________________________
>>The information in this email is confidential and inte...{{dropped:10}}
>
>_______________________________________________
>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

Jenny Drnevich, Ph.D.

Functional Genomics Bioinformatics Specialist
W.M. Keck Center for Comparative and Functional Genomics
Roy J. Carver Biotechnology Center
University of Illinois, Urbana-Champaign

330 ERML
1201 W. Gregory Dr.
Urbana, IL 61801
USA

ph: 217-244-7355
fax: 217-265-5066
e-mail: drnevich at illinois.edu