[BioC] Limma/Affy - Include expression Intensity in Final 'decideTests' results - limm2annaffy

[Atul Kakrana]

Hi Jim,

You suggestion did exactly what I wanted but number of genes in output
is different for both:

results.default <- decideTests(fit2)
write.fit(fit2,results.default,file='RESULTS2.tsv', sep = '\t')

AND

write.table(writeFit(fit2,"mouse4302", esetRMA.Reduced), "TestData.tsv",
sep = '\t', quote = FALSE, row.names = FALSE)

The decideTest gives total of ~16000 genes where as 'writeFit' gives
~20,000 genes.  I believe this is because of the default p-val cutoff in
decideTests :
decideTests(object,method="separate",adjust.method="BH",p.value=0.05,lfc=0)

As 'writeFit' currently does not support such functions (like
decideTests) I think it would be better to add expression intensities
manually to the results.

Thanks

Atul


On 04/30/2013 12:59 PM, James W. MacDonald wrote:
> Hi Atul,
>
> You might then try writeFit(), which is probably more to your liking.
> Something like
>
> write.table(writeFit(fit2, "mouse4302", esetRMA.Reduced),
> "All_data.txt", sep = "\t", quote=FALSE, row.names = FALSE)
>
> Also please note that Excel has an unfortunate habit of changing any
> gene symbol that looks like a date into a date, and this is
> irreversible (so e.g., the 1Apr gene will be converted to 4/1/2013,
> because that makes sense...).
>
> You want to import the data into Excel rather than opening, and in the
> third step of the wizard ensure that you change the format of the
> symbol column to text rather than general.
>
> Best,
>
> Jim
>
> On 4/30/2013 12:32 PM, Atul Kakrana wrote:
>> Hi James,
>>
>> Thanks for the suggestion. By using limma2annaffy I am being able to 
>> get expression intensity in final results but the problem is that a
>> separate file is generated for each comparison For Ex. if we have two
>> time points and one control than it will generate two different files.
>>
>> I was thinking of some way to add expression intensity to the results
>> from 'decideTests' that has all the comparisons at one place as that
>> is important for time series comparison. I think one way to do so is
>> just extract the expression intensities from normalized data and add
>> to final result file manually using MS Excel.
>>
>> Besides that I see an error when 'text=TRUE' option is used in
>> limma2annafyy:
>>
>> >  limma2annaffy(esetRMA.Reduced, fit2, design, adjust =
>> "none",contrast.matrix, annotation(esetRMA), pfilt = 0.01, fldfilt=
>> 1, text = TRUE, html =FALSE)
>>
>> You are going to output 3 tables,
>> With this many genes in each:
>>   1918 1950 2424
>> Do you want to accept or change these values? [ a/c ]
>> a
>> Warning message:
>> In chkPkgs(chip) :
>>    The mouse4302.db package does not appear to contain annotation data.
>>
>> The error does not appears with just html output.
>>
>> Thanks
>>
>> Atul
>>
>>
>> On 29-Apr-13 9:49 AM, James W. MacDonald wrote:
>>> Hi Atul,
>>>
>>>
>>> On 4/28/2013 11:55 PM, Atul Kakrana wrote:
>>>> Hi All,
>>>>
>>>> I am using 'affy' and 'limma' to analyze affymetrix data.
>>>>
>>>> Simplified code:
>>>>
>>>> mydata <- ReadAffy()
>>>> esetRMA <- rma(mydata)
>>>> sampletype <- c('1','1','1','2','2','2','3','3','3','4','4','4')
>>>> group <-factor(sampletype)
>>>> design<- model.matrix(~0+group)
>>>> fit <- lmFit(esetRMA, design)
>>>> contrast.matrix<-makeContrasts(B-A,C-A,D-A, levels=design)
>>>> fit2<- contrasts.fit(fit,contrast.matrix)
>>>> fit2 <- eBayes(fit2)
>>>> results.default <- decideTests(fit2)
>>>>
>>>> I get the results without any problem. But what I need is
>>>> expression intensity of probes across all samples to be included in
>>>> the results. I tried:
>>>> Intensity <- (2^(exprs(esetRMA)))
>>>>
>>>> But cannot fit data to the results
>>>> fData(results.default) <- Intensity
>>>>
>>>> Could somebody please tell me how can include expression
>>>> intensities in the 'decideTests' output?
>>>
>>> The output from decideTests() is just a matrix of 0 and 1, so you
>>> wouldn't want to append anything to that to begin with.
>>>
>>> You might take a look at limma2annaffy() in affycoretools, which
>>> does essentially what I think you want.
>>>
>>> Best,
>>>
>>> Jim
>>>
>>>
>>>>
>>>> AK
>>>>
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>>>
>>
>