Entering edit mode
Eleanor Su
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110
@eleanor-su-6460
Last seen 10.1 years ago
Hi Gordon,
I just wanted to elaborate on this email that I got from you back in
April.
This design that you sent me:
design1 <- model.matrix(~Family)
design2 <- model.matrix(~mitoHap*Treatment)
design <- cbind(design1,design2[,3:4])
Does it account for Family as a blocking factor? Also, if I increase
the
number of samples for the analysis (for example 20, instead of 10),
does
this command below change?
design <- cbind(design1,design2[,3:4])
Sorry if these seem like naive questions. I'm just trying to get a
better
understanding of the design matrix. Thanks for your help.
Best,
Eleanor
On Wed, Apr 2, 2014 at 8:25 PM, Gordon K Smyth <smyth@wehi.edu.au>
wrote:
> Dear Eleanor,
>
> design1 <- model.matrix(~Family)
> design2 <- model.matrix(~mitoHap*Treatment)
> design <- cbind(design1,design2[,3:4])
>
> Then test for the last coefficient.
>
> Best wishes
> Gordon
>
> Date: Tue, 1 Apr 2014 11:24:52 -0700
>> From: Eleanor Su <eleanorjinsu@gmail.com>
>> To: "bioconductor@stat.math.ethz.ch"
<bioconductor@stat.math.ethz.ch>
>> Subject: [BioC] Designing a model with blocking and other
interactions
>>
>> Hi All,
>>
>> I'm trying to set up a model matrix where I can look at the
interaction
>> between Treatment and mitochondrial haplotypes in my paired
samples. These
>> are the preliminary commands that I've set up:
>>
>> rawdata<-read.delim("piRNAtotalcount<10.txt", check.names=FALSE,
>>>
>> stringsAsFactors=FALSE)
>>
>>> y <- DGEList(counts=rawdata[,2:11], genes=rawdata[,1])
>>> Family<-factor(c(6,6,9,9,11,11,26,26,28,28))
>>> Treatment<-factor(c("C","H","C","H","C","H","C","H","C","H"))
>>> mitoHap<-factor(c("S","S","S","S","S","S","D","D","D","D"))
>>> data.frame(Sample=colnames(y),Family,Treatment,mitoHap)
>>>
>> Sample Family Treatment mitoHap
>> 1 6C (S) 6 C S
>> 2 6H (S) 6 H S
>> 3 9C (S) 9 C S
>> 4 9H (S) 9 H S
>> 5 11C (S) 11 C S
>> 6 11H (S) 11 H S
>> 7 26C (D) 26 C D
>> 8 26H (D) 26 H D
>> 9 28C (D) 28 C D
>> 10 28H (D) 28 H D
>>
>> design<-model.matrix(?)
>>>
>>
>> I have 10 sequencing samples from 5 different families (a treatment
and
>> control sample from each family) and two different types of
mitochondrial
>> haplotypes. How do I set up a design where I can look at the
interaction
>> between the Treatments and mitoHap while still accounting for
Family?
>>
>> Any help would be greatly appreciated. Thank you for your time.
>>
>> Best,
>> Eleanor
>>
>
>
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