[BioC] Limma topTable; fold changes look completely different to the normalized data and Limma fold change

[James W. MacDonald]

Yep. You have to remember that log2(this/that) = log2(this) - 
log2(that), so if you are in the log space you have to subtract to 
compute what would be division on the natural scale.

Best,

Jim


On 7/6/2012 4:19 PM, john herbert wrote:
> OK, I solved it using raw values and see 6.09 is log2 FC.
> Thanks.
>
> John.
>
> On Fri, Jul 6, 2012 at 9:00 PM, john herbert<arraystruggles at gmail.com>  wrote:
>> Thanks a lot James,
>> Yes, the raw PAI values are very big and I am feeding Limma log2 and
>> normalized values.
>>
>> So if I have a log2 value of 22.59173 for Tumour and a log2 value for
>> wound of 16.50009333
>> subtracting tumour - wound = 6.09 (the same number toptable comes up with)
>>
>> What is this 6.09 value, is that fold change or log2 fold change?
>>
>> I would guess fold change as 2 to the power of 6 = 64 fold change but
>> topTable labels it as logFC; please explain why?
>>
>> Thank you,
>>
>> John.
>>
>>
>>
>>
>>
>>>> Tumour average = 22.59173
>>>> Wound average = 16.50009333
>>>> Log2 Fold change = 0.453320567
>>
>>
>> On Fri, Jul 6, 2012 at 8:36 PM, James W. MacDonald<jmacdon at uw.edu>  wrote:
>>> Hi John,
>>>
>>>
>>> On 7/6/2012 3:12 PM, john herbert wrote:
>>>> Dear all,
>>>> I have a problem with the log Fold changes calculated in Limma. I am
>>>> using protein abundance index of proteomic data
>>>> The log2 of this data is normally distributed and after log2, I use
>>>> quantile normalization
>>>>
>>>> This is then the data matrix I use as input to Limma
>>>>
>>>>> class(norm_ctw)
>>>> [1] "matrix"
>>>>
>>>>> dim(norm_ctw)
>>>> [1] 683   9
>>>> design<- model.matrix(~ 0+factor(c(1,1,1,2,2,2,3,3,3)))
>>>> colnames(design)<- c("cam", "tumour", "wound")
>>>> fit<- lmFit(norm_ctw, design)
>>>>
>>>> contrast.matrix<- makeContrasts(tumour-wound, tumour-cam, levels=design)
>>>> fit2<- contrasts.fit(fit, contrast.matrix)
>>>> fit2<- eBayes(fit2)
>>>>
>>>> topTable(fit2, coef=1, adjust="BH")
>>>>
>>>> Taking one gene as an example. NAMPT in tumour versus wound and
>>>> calculating fold change by hand of normalized data;
>>>>
>>>>> norm_ctw["NAMPT",]
>>>>       cam1     cam2     cam3  tumour1  tumour2  tumour3   wound1
>>>> wound2   wound3
>>>> 19.80164 19.46355 19.26075 22.75347 22.62651 22.39521 16.17398 16.60262
>>>> 16.72368
>>>>
>>>> In Excel, calculating log2 fold change using Average of Tumour/Average
>>>> of wound =
>>>> T1 22.75347     T2 22.62651     T3 22.39521     W1 16.17398     W2
>>>> 16.60262     W3 16.72368
>>>> Tumour average = 22.59173
>>>> Wound average = 16.50009333
>>>> Log2 Fold change = 0.453320567
>>>
>>> Wait a minute... Are these data logged or not? You say above that you take
>>> logs and then normalize, and then you present some data that would be really
>>> big if they were log2 variates (but then I have no idea of the scale for
>>> protein abundance data).
>>>
>>> Anyway, you are acting like these data are not logged, whereas limma assumes
>>> they are. So you either have to take logs before feeding into limma, or you
>>> need to compute the fold change by subtraction (if the data above are
>>> already logged).
>>>
>>> Best,
>>>
>>> Jim
>>>
>>>
>>>
>>>>
>>>> However, from TopTable....
>>>>> topTable(fit2,coef=1)
>>>>             ID     logFC  AveExpr         t      P.Value    adj.P.Val
>>>> B
>>>> 431    NAMPT  6.091632 19.53349  20.16810 2.688444e-09 1.750946e-06
>>>> 11.409857
>>>>
>>>>>  From toptable, NAMPT has an apparent log2 FC of 6 or 64 fold change
>>>> but that is impossible right??
>>>>
>>>> Please can someone explain if I am using Limma wrong or how the fold
>>>> change can be massively different between "by hand" and with Limma.
>>>>
>>>> Thank you very much for any advice.
>>>>
>>>> John.
>>>>
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>>>
>>> --
>>> James W. MacDonald, M.S.
>>> Biostatistician
>>> University of Washington
>>> Environmental and Occupational Health Sciences
>>> 4225 Roosevelt Way NE, # 100
>>> Seattle WA 98105-6099
>>>

-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099