Hi James,


> 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.
>

This is exactly what I want, so thanks to your clear restate.



> 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)
>


OK I still to progress on the differences between interaction model and
additive model (with which I'm more familiar)
Do you think it will be useful to set up an Intercept ?
design <- model.matrix(~0+drug*lifeinteg)

Again many for your time and your help.

Bests
--
Dave




> 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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