[BioC] Colourful way of visualising differential analysis results

[Daniel Brewer]

Hi,

That sounds great.  I am not sure exactly how you can do it and whether
it is applicable to the experiment.  Could you provide a simple example?

The experiment information is below and I am interested in the PC3M vs
knockdown comparison

Targets file:
SlideNumber	ArrayNumber	FileName	Name	Cy3	Cy5
1	1	Input/1_1.txt	1_1	Scramble	Knockdown
1	2	Input/1_2.txt	1_2	Knockdown	PC3M
1	3	Input/1_3.txt	1_3	PNT2	PC3M
1	4	Input/1_4.txt	1_4	Pooled	PNT2
2	2	Input/2_2.txt	2_2	PC3M	Scramble
2	3	Input/2_3.txt	2_3	PNT2	Scramble
3	1	Input/3_1.txt	3_1	PC3M	Pooled
3	2	Input/3_2.txt	3_2	Pooled	Knockdown
3	3	Input/3_3.txt	3_3	Scramble	Pooled
3	4	Input/3_4.txt	3_4	Knockdown	PNT2

PC3M = the control cell line
Knockdown = PC3M with an siRNA knockdown vector
Scramble = PC3M with a vector with a scrambled sequence
PNT2 = Another cell line (not of interest here)
Pooled = poll of knockdowns before you get specific clone, intermediate
between PCM3 and knockdown - a hetrogenious group (not considered here)

> design
      Knockdown PNT2 Pooled Scramble
 [1,]         1    0      0       -1
 [2,]        -1    0      0        0
 [3,]         0   -1      0        0
 [4,]         0    1     -1        0
 [5,]         0    0      0        1
 [6,]         0   -1      0        1
 [7,]         0    0      1        0
 [8,]         1    0     -1        0
 [9,]         0    0      1       -1
[10,]        -1    1      0        0

Thanks Dan

Yannick Wurm wrote:
> Hi Dan,
> 
> for this kind of thing, I'll fit another limma model just to obtain
> estimates of what needs to be visualized...
> In one case, I needed to separately visualize expression levels from
> each biological replicate, but variability was such that I had grouped
> them together in my model. To estimate expression levels for each
> biological replicate, I recreated a targets file, separating each
> biological replicate by name. Then calculated a fit, and asked for
> contrasts between each sample and one RNA which I chose as reference. 
> (centering expression levels within each gene afterwards works too)
> 
> Despite a complex design it was thus possible to generate a heatmap
> where each of the 8 biological replicated RNAs from 3 different
> conditions where represented separately.
> 
> hope this helps,
> 
> yannick
> 
> 
> 
> On Nov 10, 2008, at 17:33 , Daniel Brewer wrote:
> 
>> Dear all,
>>
>> I am doing some work on a two-colour microarray (Agilent) experiment and
>> I have used limma to do some differential analysis.  The person I am
>> doing this work was keen to have a heatmap of the differentially
>> expressed genes expression levels.  Unfortunately, the design is rather
>> complex and random (closer to a loop design than a common reference) so
>> its not possible to produce a traditional heatmap.  I was wondering if
>> anyone had any suggestions of a colourful way to show that the
>> expression of the two groups are different?
>>
>> In particular I was thinking that there must be estimates of the
>> expression and error in each group by the linear model, but couldn't
>> work out how to find these.
>>
>> Thanks
>>
>> Dan



-- 
**************************************************************

Daniel Brewer

Institute of Cancer Research
Molecular Carcinogenesis
MUCRC
15 Cotswold Road
Sutton, Surrey SM2 5NG
United Kingdom

Tel: +44 (0) 20 8722 4109
Fax: +44 (0) 20 8722 4141

Email: daniel.brewer at icr.ac.uk

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The Institute of Cancer Research: Royal Cancer Hospital, a charitable Company Limited by Guarantee, Registered in England under Company No. 534147 with its Registered Office at 123 Old Brompton Road, London SW7 3RP.

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