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Yannick Wurm
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@yannick-wurm-2314
Last seen 10.2 years ago
Hi Dan,
my apologies for the slow reply.
How many different PC3M samples were used? Only 1? So you want a
single-column heatmap (with xxxx rows, 1 per spot?)
Then just make a limma model
then use makeContrasts(PC3M-Knockdown, design)
then once you've done lmFit,
you'll find the relative expression values in the
"coefficients" part
of myFitObject. Access it via myFitObject$coefficients
Alternatively, if you want one heatmap column per PC3M you hybridized,
you can calculate them by hand:
+go to your MA object, and use the log2 relative expression
levels
from MA$M (you have one column per microarray).
+To compare Knockdown against PC3M,
- use array 1_2 data as is:
MA$M[,2]
- calculate Knockdown-PC3M a second time via arrays
1_3 and 3_4:
MA$M[,10]+MA$M[,3]
- calculate Knockdown-PC3M again via arrays 2_2 and
1_1:
-MA$M[,1] -MA$M[,5]
- and then again via arrays 3_1 and 3_2
heatmap(cbind(MA$M[,2], MA$M[,10]+MA$M[,3], -MA$M[,1] -MA$M[,5], ...))
Best,
yannick
On Nov 11, 2008, at 11:24 AM, Daniel Brewer wrote:
> 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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