[BioC] Limma time course analysis - defining comparisons

[James W. MacDonald]

Hi Helen,

Helen Zhou wrote:
> Dear Jim
> 
> Thanks you for your answer. As I understand you are
> recommending me to do direct comparisons between for
> example 12-4h and 24-12h. However, could there not in
> theory be a gene that was up a little bit in 12vs4h
> and 24vs12h, so that the difference for neither of
> these would be large enough to be significant, but for
> 24vs4h the combined change might be significant? In
> that case I guess I would need all 3 comparisons?

Yes. The 'standard' linear modeling strategy is to fit the model and see 
if you have a significant F-statistic, then come back and do contrasts 
to see which particular comparison(s) is/are contributing to that 
significance. The general idea being that you want to limit the number 
of comparisons you are making so multiplicity is less of a problem.

However, with microarray data this isn't usually what people do. 
Instead, they usually try to minimize the multiplicity by filtering out 
uninteresting reporters prior to making comparisons (based on variance, 
P/M/A calls, IQR, etc) and then computing all contrasts that they are 
interested in with the reporters that remain.

You might consider using decideTests() using the 'nestedF' option - this 
is intended to correctly detect differential expression when two or more 
contrasts are significant, so in the case you mention may classify all 
three contrasts as significant.

Best,

Jim


> 
> Thanks you
> Helen
> 
> --- "James W. MacDonald" <jmacdon at med.umich.edu>
> wrote:
> 
>> Hi Helen,
>>
>> Helen Zhou wrote:
>>> Dear Sir/Madam
>>>
>>> I am trying to analyse a short time series,
>> roughly
>>> following section 8.8 in the limma user guide. I
>> am
>>> interested in differences between all time points.
>> I
>>> am not sure whether I have to make all the
>> pariwise
>>> comparisons directly, or whether they can be done
>>> indirectly as well.
>>>
>>> For example, if I want to compare to time points,
>> what
>>> is the differences between the two methods listed
>>> below.
>>>
>>> library(bronchialIL13)
>>> # Just for the IL13 samples
>>> data <- HAHrma[,7:15]
>>> # Design
>>> targets	<-
>>>
> c("h12","h12","h12","h24","h24","h24","h4","h4","h4")
>>> lev	<- c("h12","h24","h4")
>>> f	<- factor(targets, levels=lev)
>>> design	<- model.matrix(~0+f)
>>> colnames(design)	<- lev
>>> fit <- lmFit(data, design)
>>> # 2-step contrasts, used to indirectly get 24 to 4
>>> hours as well as the other two comparisons
>>> contrasts <- makeContrasts("h24-h12", "h12-h4",
>>> levels=design)
>>> fit2 <- contrasts.fit(fit, contrasts)
>>> fit2 <- eBayes(fit2)
>>> # Direct contrast of 24 to 4 hours
>>> contrasts2 <- makeContrasts("h24-h4",
>> levels=design)
>>> fit3 <- contrasts.fit(fit, contrasts2)
>>> fit3 <- eBayes(fit3)
>>> # Comparison
>>> topTable(fit2, coef=1:2)
>>> topTable(fit3, coef=1)
>> In the first case you are asking the question 'which
>> reporters are 
>> different in either h24 vs h4 _or_ h12 vs h4',
>> whereas in the second 
>> case you are asking 'which reporters are different
>> between H24 and h4'.
>>
>> It is entirely possible that you could have a gene
>> that isn't different 
>> between h24 and h4, but is different at h12. This
>> would show up in the 
>> first comparison but not the second, so if you want
>> to compare time 
>> points you are better off making direct contrasts
>> rather than using the 
>> F-statistic for multiple contrasts (which will then
>> require the 
>> additional step of figuring out which contrast(s)
>> caused the statistic 
>> to be significant).
>>
>> Best,
>>
>> Jim
>>
>>
>>> More or less the same probe sets are present, but
>> in
>>> different order and with different p values. Is
>> the
>>> difference because using coef=1:2 will go via an
>>> F-test? And if I want the change from 24h-0h as
>> well
>>> as 42-12h and 12-4h, is it most correct for me to
>>> specify that contrast directly? In my actual
>>> experiment I have 4 time points, so will it be
>> enough
>>> for me with 3 possible comparisons, or will I have
>> to
>>> write all the 6 possible combinations?
>>>
>>> Thank you in advance for all your help.
>>>
>>> Yours truly
>>> Mrs Helen Zhou
>>>
>>> P.S. I think this might have been mentioned on the
>>> list before, but I could not find the email. In
>> that
>>> case, please excuse me for repeating this.
>>>
>>> _______________________________________________
>>> 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
>> -- 
>> James W. MacDonald, M.S.
>> Biostatistician
>> Affymetrix and cDNA Microarray Core
>> University of Michigan Cancer Center
>> 1500 E. Medical Center Drive
>> 7410 CCGC
>> Ann Arbor MI 48109
>> 734-647-5623
>>
> 
> 
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-- 
James W. MacDonald, M.S.
Biostatistician
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623