Dear Naomi,

Sorry I made a mistake, I really want to fit the interaction model, I  was
tired and I forgot to add the interaction term. If I have two factors I have
to count for the effects of each and the interaction right? Why did I I
runned of d.? How can I analyze this if the problem is no replicates? Can I
use a random block design?

thanks for your opinion

Kind regards,
Andreia

On Sat, Jan 30, 2010 at 3:08 AM, Naomi Altman <naomi@stat.psu.edu> wrote:

> The reason you have no d.f. for testing is that you did not fit the model
> below.  You fitted the model with a separate mean for each treatment
> combination, which is equivalent to fitting the model which includes
> interaction.  So you used up all of your d.f.
>
> Regards,
> Naomi
>
>
> At 11:32 AM 1/29/2010, Andreia Fonseca wrote:
>
>> Dear list,
>>
>>
>> I am going to analyze data with the design shown below. I do not have
>> replicates, but is a complete 2x3 factorial design and therefore I should
>> be
>> able to fit a linear model
>>
>> y=mean+Celltype+Treatment+error for each of gene and then do multiple
>> testing correction, right? So, why after running,
>>
>> TS<-paste(raw_files$Cell_Type, raw_files$Treatment, sep=".")
>> > TS<-factor(TS, levels=c("NS.control1", "NS.H1",
>> > "NS.H2","S.control2","S.H1","
>> S.H2"))
>> > design<-model.matrix(~0+TS)
>> > contrasts<-makeContrasts(TSS.H1-TSS.H2, TSNS.H1-TSNS.H2,
>> > (TSNS.H1-TSNS.H2)-(TSS.H1-TSS.H2),levels=design)
>> > sr.norm2<-sr.norm[order(featureNames(sr.norm)),]
>> > qDE.limma<-limmaCtData(sr.norm2,design=design,contrasts=contrasts,
>> > spacing=1)
>> >
>> > I am getting an error message
>> >
>> > Error in ebayes(fit = fit, proportion = proportion, stdev.coef.lim =
>> > stdev.coef.lim) :
>> >   No residual degrees of freedom in linear model fits
>>
>>
>> I get this error?
>>
>> should I only make a two sample t-test? and I can't fit a linear model?
>>
>> Thanks for your help!
>>
>> Kind regards
>>
>> Andreia
>>
>>
>>
>> On Thu, Jan 28, 2010 at 9:54 PM, Heidi Dvinge <heidi@ebi.ac.uk> wrote:
>>
>> > Hi Andreia,
>> >
>> > > Hello Heidi,
>> > >
>> > > my question is about the classification of unreliable estimates e
>> > > setCategory. I saw the code and it seems that you are estimating just
>> the
>> > > classical c.i. based in the variation of the data, right?
>> >
>> > yep
>> >
>> > > I have a new
>> > > question though concerning qDE.limma, as I told you I have a factorial
>> > > design, so I have created a factorial design form the example data
>> from
>> > > HT-qPCR
>> > >
>> > >  TSNS.control1 TSNS.H1 TSNS.H2 TSS.control2 TSS.H1 TSS.H2
>> > > 1             1         0         0            0        0        0
>> > > 2             0         1         0            0        0        0
>> > > 3             0         0         1            0        0        0
>> > > 4             0         0         0            1        0        0
>> > > 5             0         0         0            0        1        0
>> > > 6             0         0         0            0        0        1
>> > >
>> > > TS<-paste(raw_files$Cell_Type, raw_files$Treatment, sep=".")
>> > > TS<-factor(TS, levels=c("NS.control1", "NS.H1",
>> > > "NS.H2","S.control2","S.H1","S.H2"))
>> > > design<-model.matrix(~0+TS)
>> > > contrasts<-makeContrasts(TSS.H1-TSS.H2, TSNS.H1-TSNS.H2,
>> > > (TSNS.H1-TSNS.H2)-(TSS.H1-TSS.H2),levels=design)
>> > > sr.norm2<-sr.norm[order(featureNames(sr.norm)),]
>> > > qDE.limma<-limmaCtData(sr.norm2,design=design,contrasts=contrasts,
>> > > spacing=1)
>> > >
>> > > I am getting an error message
>> > >
>> > > Error in ebayes(fit = fit, proportion = proportion, stdev.coef.lim =
>> > > stdev.coef.lim) :
>> > >   No residual degrees of freedom in linear model fits
>> > >
>> > >
>> > > is it because this that is not adequate for this design? or I have the
>> > > wrong
>> > > command?
>> > >
>> > Your approach as such seems valid, but the problem is that you have no
>> > replicate arrays. Which means that unfortunately the limma functions
>> won't
>> > work, since there's no way to do statistical testing.
>> >
>> > Maybe someone on the list can help if we know a little more about your
>> > arrays/intention. It looks e.g. like you don't use your two control
>> > samples at all?
>> >
>> > Cheers
>> > \Heidi
>> >
>> > > thanks Andreia
>> > >
>> > >
>> > >
>> > >
>> > > On Wed, Jan 27, 2010 at 11:26 PM, Heidi Dvinge <heidi@ebi.ac.uk>
>> wrote:
>> > >
>> > >> Hello Andreia,
>> > >>
>> > >> sorry for the delay in answering. Just to be clear, what confidence
>> > >> interval are you referring to? The confidence intervals plotted in
>> > >> plotCtOverview? The deviations used to assign categories in then
>> > >> filtering
>> > >> the data?
>> > >>
>> > >> Cheers
>> > >> \Heidi
>> > >>
>> > >> P.S. By the way, just in case you're new to R, you can always see the
>> > >> source code of a function, by just typing the function name in the
>> > >> terminal, without "?" before or "()" after.
>> > >>
>> > >> > Hi Heidi,
>> > >> >
>> > >> >
>> > >> > sorry is just to say that I have tested to read the file with two
>> > >> columns
>> > >> > for the two factors and that part works!!! So now I will move on
>> for
>> > >> the
>> > >> > other functions, plotCtOverview works fine! Now can you just answer
>> to
>> > >> the
>> > >> > confidence intervals question?
>> > >> >
>> > >> > Thanks
>> > >> > Andreia
>> > >> > On Wed, Jan 27, 2010 at 10:24 AM, Andreia Fonseca
>> > >> > <andreia.fonseca@gmail.com
>> > >> >> wrote:
>> > >> >
>> > >> >> Hi Heidi,
>> > >> >>
>> > >> >>
>> > >> >> my question is how should be the format of the files.txt file, so
>> > >> that
>> > >> >> HTqPCR can read in the information of the two different factors,
>> > >> should
>> > >> >> it
>> > >> >> be like the example I wrote below? And what about the confidence
>> > >> >> intervals
>> > >> >> to filter data, how does the package estimates them?
>> > >> >> Cheers
>> > >> >> Andreia
>> > >> >>
>> > >> >>
>> > >> >> On Tue, Jan 26, 2010 at 10:23 PM, Heidi Dvinge <heidi@ebi.ac.uk>
>> > >> wrote:
>> > >> >>
>> > >> >>> Hello Andreia,
>> > >> >>>
>> > >> >>> actually, HTqPCR can handle multi-factor design, there's just no
>> > >> >>> example
>> > >> >>> of that in the vignette (will consider adding it in the next
>> > >> revision).
>> > >> >>>
>> > >> >>> The function limmaCtData takes all the arguments that you'd use
>> if
>> > >> you
>> > >> >>> were analysing microarray data using lmFit and contrasts.fit from
>> > >> the
>> > >> >>> limma package.  You need to specify the design and contrast
>> matrix
>> > >> >>> yourself though. As I recall, the limma user's guide has a couple
>> of
>> > >> >>> example involving factorial design.
>> > >> >>>
>> > >> >>> HTH
>> > >> >>> \Heidi
>> > >> >>>
>> > >> >>> > Dear list,
>> > >> >>> >
>> > >> >>> > Soon I will receive data from the qpcr Exicon platform to
>> analyze
>> > >> and
>> > >> >>> I
>> > >> >>> > have
>> > >> >>> > been playing around with HTqPCR package, however from the
>> vignete,
>> > >> it
>> > >> >>> > seems
>> > >> >>> > that is only capable of deleting with data design of one
>> factor,
>> > >> how
>> > >> >>> do
>> > >> >>> I
>> > >> >>> > handle it with a factorial design, namely how do I read the
>> data
>> > >> and
>> > >> >>> > create
>> > >> >>> > the model.matrix, the examples only consider one factor.
>> Another
>> > >> >>> question
>> > >> >>> > is
>> > >> >>> > concerning part 5 of the vignete, how are the Confidence values
>> > >> >>> estimated?
>> > >> >>> > is is based in the variance of the data?
>> > >> >>> >
>> > >> >>> > In order for you to understand my doubts here is my design is a
>> > >> 2x3
>> > >> >>> > design,
>> > >> >>> > I don't have replicates, but each file has the CT values for
>> each
>> > >> >>> gene
>> > >> >>> > frome
>> > >> >>> > pooled RNA of 10 patients.
>> > >> >>> >             factor1   factor2
>> > >> >>> > file1.txt  NS        C
>> > >> >>> > file2.txt  NS        H1
>> > >> >>> > file3.txt  NS        H2
>> > >> >>> > file4.txt    S        C
>> > >> >>> > file5.txt    S        H1
>> > >> >>> > file6.txt    S        H2
>> > >> >>> >
>> > >> >>> >
>> > >> >>> > Thanks for your help.
>> > >> >>> > with kind regards,
>> > >> >>> > Andreia
>> > >> >>> >
>> > >> >>> >
>> > >> >>> > --
>> > >> >>> > --------------------------------------------
>> > >> >>> > Andreia J. Amaral
>> > >> >>> > Unidade de Imunologia Clínica
>> > >> >>> > Instituto de Medicina Molecular
>> > >> >>> > Universidade de Lisboa
>> > >> >>> > email: andreiaamaral@fm.ul.pt
>> > >> >>> >          andreia.fonseca@gmail.com
>> > >> >>> >
>> > >> >>> >       [[alternative HTML version deleted]]
>> > >> >>> >
>> > >> >>> > _______________________________________________
>> > >> >>> > Bioconductor mailing list
>> > >> >>> > Bioconductor@stat.math.ethz.ch
>> > >> >>> > https://stat.ethz.ch/mailman/listinfo/bioconductor
>> > >> >>> > Search the archives:
>> > >> >>> >
>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>> > >> >>>
>> > >> >>>
>> > >> >>>
>> > >> >>
>> > >> >>
>> > >> >> --
>> > >> >> --------------------------------------------
>> > >> >> Andreia J. Amaral
>> > >> >> Unidade de Imunologia Clínica
>> > >> >> Instituto de Medicina Molecular
>> > >> >> Universidade de Lisboa
>> > >> >> email: andreiaamaral@fm.ul.pt
>> > >> >>          andreia.fonseca@gmail.com
>> > >> >>
>> > >> >
>> > >> >
>> > >> >
>> > >> > --
>> > >> > --------------------------------------------
>> > >> > Andreia J. Amaral
>> > >> > Unidade de Imunologia Clínica
>> > >> > Instituto de Medicina Molecular
>> > >> > Universidade de Lisboa
>> > >> > email: andreiaamaral@fm.ul.pt
>> > >> >          andreia.fonseca@gmail.com
>> > >> >
>> > >>
>> > >>
>> > >>
>> > >
>> > >
>> > > --
>> > > --------------------------------------------
>> > > Andreia J. Amaral
>> > > Unidade de Imunologia Clínica
>> > > Instituto de Medicina Molecular
>> > > Universidade de Lisboa
>> > > email: andreiaamaral@fm.ul.pt
>> > >          andreia.fonseca@gmail.com
>> > >
>> >
>> >
>> >
>>
>>
>> --
>> --------------------------------------------
>> Andreia J. Amaral
>> Unidade de Imunologia Clínica
>> Instituto de Medicina Molecular
>> Universidade de Lisboa
>> email: andreiaamaral@fm.ul.pt
>>         andreia.fonseca@gmail.com
>>
>>        [[alternative HTML version deleted]]
>>
>> _______________________________________________
>> Bioconductor mailing list
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>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>> Search the archives:
>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>>
>
> Naomi S. Altman                                814-865-3791 (voice)
> Associate Professor
> Dept. of Statistics                              814-863-7114 (fax)
> Penn State University                         814-865-1348 (Statistics)
> University Park, PA 16802-2111
>
>


-- 
--------------------------------------------
Andreia J. Amaral
Unidade de Imunologia Clínica
Instituto de Medicina Molecular
Universidade de Lisboa
email: andreiaamaral@fm.ul.pt
         andreia.fonseca@gmail.com

	[[alternative HTML version deleted]]

