Entering edit mode
Dear Vladimir,
You are correct that topTable() has been ignoring the lfc argument
when
the ranking is by F-statistic, i.e., when ranking by several contrasts
simultaneously.
Alex is correct as to the reason for this -- it was just ambiguous
what
should be done. However the behaviour should have been explained more
fully in the documentation.
I now have committed an update to the topTable() function so that the
lfc
cutoff will now be applied to the minimum absolute logFC for the
contrasts
being tested when ranking by F-statistic. The behaviour is now
analogous
to decideTests(). Genes will be kept in the table if any contrast
satisfies the cutoff.
I committed this change to the developmental version of limma a few
days
ago. I committed the change to the official release version of limma
just
a few minutes ago, so it should be able for download from Bioconductor
in
a day or so.
Normally decideTests() mimics the behavour of topTable() applied to
individual contrasts. However you can recover the same genes that
appear
in an F-statistic topTable() ranking by using:
result <- decideTests(fit, method="nestedF", ...)
which.genes <- apply(result, 1, any)
The effects of p-value and lfc cutoffs should now be the same in both
topTable() and decideTests().
Best wishes
Gordon
> Date: Sat, 21 Jan 2012 04:52:10 +0000
> From: Vladimir Zhurov <vzhurov2 at="" uwo.ca="">
> To: <bioconductor at="" stat.math.ethz.ch="">
> Subject: Re: [BioC] Problem with limma's topTable lfc filter when
more
> than 1 contrast is in output
>
> Alex Gutteridge <alexg at="" ...=""> writes:
>
>>
>> On 20.01.2012 05:11, Vladimir Zhurov wrote:
>>>> ...
>>>
>>> Dear Bioconductors,
>>>
>>> I am having the following problem which can be due to a
>>> misunderstanding, or an actual problem with topTable function in
limma
>>> package.
>>>
>>> As far as I understand lfc and p filters should work together in
>>> filtering topTable results. Am I correct in this regard?
>>>
>>> If it is an intended situation then the problem is the following:
when
>>> more than one contrasts is reported lfc filter does not affect the
>>> output. Which is shown in the sample R session below.
>>>
>>> I would appreciate you help.
>>>
>>> Regards.
>>>
>>> Vladimir.
>>>
>>
>> Hi Vladimir,
>>
>> I think the issue maybe that it is not clear (to me anyway!) what
>> result one would expect with a lfc filter on a table with multiple
>> contrasts. Should rows where all contrasts are above the cutoff be
>> reported? Or where any are? It doesn't seem to be explicit in the
docs,
>> but my assumption is that to avoid confusion topTable ignores lfc=
in
>> the case you describe.
>>
>> Perhaps decideTests() is what you are really looking for? You can
then
>> index a topTable generated data.frame with the results of
decideTests.
>> E.g (pseudo-code not tested!)
>>
>> tt = topTable(fit,p.value=1,number=Inf,sort.by="none")
>> dt = decideTests(fit,p.value=0.05,lfc=1)
>>
>> tt[dt[,1] != 0 & dt[,2] != 0 & dt[,3] !=0,] #Gives rows where all
>> contrasts pass filter (assuming 3 contrasts)
>> tt[dt[,1] != 0 | dt[,2] != 0 | dt[,3] !=0,] #Gives rows where any
>> contrast passes filter
>>
>
> Alex,
>
> Thank you for your input. I was considering decideTests but wanted
to check
> whether there is something that can be done with topTable. I think
that it would
> be nice at very least to explain intended behavior in more details
in the manual
> for a case of multiple contrasts comparison.
>
> Anyway, I ended up with the following workaround (lets say lfc=1,
p=0.05 and no
> adjustment of p value):
>
> tt.all<-topTable(fit.eb, sort.by="none", number=Inf,
adjust.method="none")
> dt<-decideTests(fit.eb, lfc=1, p=0.05, adjust.method="none",
method="separate")
> rs<-rowSums(abs(dt))
> tt<-tt.all[rs >= 1,] # a single contrast above lfc will be
sufficient
>
> One may think that you are done at this point. However, decideTests
with
> method="separate" recapitulates topTable performed on individual
contrasts. As a
> result there are extra probes which will be reported and will have p
value above
> cut-off when topTable is done across multiple comparisons. They need
to be
> further filtered out.
>
> tt.filt<-tt[tt$adj.P.Val < 0.05,]
>
> Regards.
>
> Vladimir.
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