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

[James W. MacDonald]

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