[BioC] Differential drug effect on clinical groups

James W. MacDonald jmacdon at uw.edu
Wed Jun 20 15:36:00 CEST 2012


Hi Dave,

On 6/19/2012 5:10 PM, Dave Canvhet wrote:
> Dear all,
>
>
> I have 32 transcriptomics profile of A. thaliana (single color), among
> which15 received a drug treatment and 15 are the control group. For all
> these samples, 2 biological observations were also obtained :
> - life time of the plant (short or long)
> - expression of an integrine (with or without)
>
> I would like to get the following contrast :
> (short life time without integrine) versus (long life time with integrine)
> into treated samples
> versus
> (short life time without integrine) versus (long life time with integrine)
> into control samples

This isn't really clear, and I might be way off base with this answer, 
but it looks to me like you are after an interaction term. If I were to 
restate, I would say that you are looking for genes that react 
differently to treatment between the long lived integrine positive 
samples and the short lived integrine negative samples.

If true, this isn't difficult to set up, although I wouldn't do it the 
way you are. Personally, I would combine the samples into four types, 
based on life and integrine (where for brevity, life is long/short and 
integrine is +/-):

long+
short+
long-
short-

Now your interaction as I understand it will only utilize the long+ and 
short- samples, so you would restrict your samples to just those samples 
that fulfill those criteria. Then you could make a lifeinteg factor that 
is long+ and short- and create a design matrix

design <- model.matrix(~drug*lifeinteg)

and the lifeinteg2 coefficient is the interaction, and gives you the 
genes that react differently to the drug based on being long+ or short-.

Best,

Jim



>
>
> I've set up my design matrix (target is below):
>
> drug = as.factor(targetATH$drug)
>
> integr  = as.factor(targetATH$integrin)
>
> lifetime = as.factor(targetATH$lifetime)
>
> design = model.matrix(~drug+integr+lifetime)
>
> I can't figure out how to set up the correct contrast matrix to get the
> coefficient I want.
> I would be very grateful if you could give any pieces of advices for that.
> I hope I have enough sample to get enough power to detect some genes.
>
>
> many thanks by advance, best regards,
> --
> Dave
>
>
>   target :
>> targetATH
>         FileName drug lifetime integrin
> 1   sample1.cel    Y        S        +
> 2   sample2.cel    Y        S        +
> 3   sample3.cel    Y        S        +
> 4   sample4.cel    Y        S        +
> 5   sample5.cel    Y        L        +
> 6   sample6.cel    Y        L        +
> 7   sample7.cel    Y        L        +
> 8   sample8.cel    Y        L        +
> 9   sample9.cel    Y        S        -
> 10 sample10.cel    Y        S        -
> 11 sample11.cel    Y        S        -
> 12 sample12.cel    Y        S        -
> 13 sample13.cel    Y        L        -
> 14 sample14.cel    Y        L        -
> 15 sample15.cel    Y        L        -
> 16 sample16.cel    Y        L        -
> 17 sample17.cel    N        S        +
> 18 sample18.cel    N        S        +
> 19 sample19.cel    N        S        +
> 20 sample20.cel    N        S        +
> 21 sample21.cel    N        L        +
> 22 sample22.cel    N        L        +
> 23 sample23.cel    N        L        +
> 24 sample24.cel    N        L        +
> 25 sample25.cel    N        S        -
> 26 sample26.cel    N        S        -
> 27 sample27.cel    N        S        -
> 28 sample28.cel    N        S        -
> 29 sample29.cel    N        L        -
> 30 sample30.cel    N        L        -
> 31 sample31.cel    N        L        -
> 32 sample32.cel    N        L        -
>
> 	[[alternative HTML version deleted]]
>
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-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099



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