[BioC] Limma -time course - no replicates

[Yair Benita]

Hi Naomi,
Thank you for pointing out this example, its really useful.
Can you explain the meaning of the p.value and F.p.value in this case? Which
one should be used?

time=1:10
design=model.matrix(~time)
fit=eBayes(lmFit(data, design))

Thank you.
Yair



on 6/8/10 3:53 PM, Naomi Altman at naomi at stat.psu.edu wrote:

> time=1:10
> design=model.matrix(~time)
> 
> 
> 
> At 12:28 PM 6/8/2010, Lana Schaffer wrote:
>> Naomi,
>> Thanks.
>> Can you give an example how to set up the design matrix?
>> Lana
>> 
>> ________________________________________
>> From: Naomi Altman [naomi at stat.psu.edu]
>> Sent: Tuesday, June 08, 2010 7:49 AM
>> To: Lana Schaffer; Naomi Altman; bioconductor at stat.math.ethz.ch
>> Subject: Re: [BioC] Limma -time course - no replicates
>> 
>> You can use LIMMA.  The key is to have time be a continuous variable,
>> not a factor.  So time (or a function of time) is entered into the
>> design matrix, instead of +/- 1 or 0.
>> 
>> --Naomi
>> 
>> At 02:11 AM 6/6/2010, Lana Schaffer wrote:
>>> Naomi,
>>> Can you please suggest a routine or software for us to use?
>>> Lana
>>> 
>>> ________________________________________
>>> From: Naomi Altman [naomi at stat.psu.edu]
>>> Sent: Friday, June 04, 2010 6:49 PM
>>> To: Lana Schaffer; bioconductor at stat.math.ethz.ch
>>> Subject: Re: [BioC] Limma -time course - no replicates
>>> 
>>> Only if you consider this to be a regression on a function of time,
>>> instead of an ANOVA.
>>> 
>>> --naomi
>>> 
>>> At 07:12 PM 6/4/2010, Lana Schaffer wrote:
>>>> Hi,
>>>> We are trying to use Limma code for a Time Course Experiment without
>>>> Replicates for 4 times.  From looking at the manual, looks like don't
>>>> Need replicates.  But the ebayes routine complains about no residual
>>>> Degrees of freedom.
>>>> Can we use Limma for Time Course without replicates?
>>>> Lana
>>>> 
>>>> _______________________________________________
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>>> 
>>> 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
>>> 
>>> _______________________________________________
>>> Bioconductor mailing list
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>> 
>> 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
> 
> 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
> 
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor