[BioC] Limma package: problem with p-value and t

Julie Zhu julie.zhu at umassmed.edu
Thu Sep 17 23:01:20 CEST 2009


Hi James,

Thanks you so much for helping me solving the mystery!  Could you please
explain why the degree freedom is so large? I only have 4 arrays, so total 3
df (n-1). One is used for estimating dye effect, 1 is used for estimating
mutant effect, so the residual is 1 df. Why is there an additional of
2.397083 df added? Is it because the information borrowing from the
neighboring genes? How is the df.prior calculated? Thanks so much for
sharing your knowledge!

Best regards,

Julie


On 9/17/09 4:50 PM, "James W. MacDonald" <jmacdon at med.umich.edu> wrote:

> 
> 
> Julie Zhu wrote:
>> Dear Gordon,
>> 
>> I noticed that there is inconsistency between the t and p.value on the
>> topTable output using Limma package to analyze a dye swap two channel array
>> experiment. 
>>         logFC  AveExpr        t      P.Value  adj.P.Val        B
>> 1401 3.216254 11.74137 22.49546 1.041470e-05 0.07874703 3.435097
>> 1537 3.344735 11.88007 18.07448 2.702061e-05 0.07874703 2.951114
>> 
>> The two-tailed p-value for t=22.49546 with df=1 would be 0.028
>> 2*pt(-abs(22.49546),df=1), but the P.Value in the above output is 1.04e-05.
>> Did I miss something? Could you please explain the inconsistency? Thanks!
> 
> The degrees of freedom will be somewhere around 3, but a bit larger
> because of the ebayes fit. You can get the actual value from your
> MArrayLM object, so what you really want is
> 
> 2*pt(-abs(22.49546), fit$df.prior + fit$df.residual[1])
> 
> assuming you did something like
> 
> fit <- lmFit(<stuff>)
> fit <- eBayes(fit)
> 
> Best,
> 
> Jim
> 
> 
>> 
>> Here is the design matrix and relevant code snippets.
>> 
>>    Dye mutant
>>    1     -1
>>    1     -1
>>    1      1
>>    1      1
>> 
>> design = cbind(Dye=1, mutant = c(-1,-1,1,1))
>> fit = lmFit(MA, design)
>> ### MA is a MAlist object
>> fit3 = eBayes(fit)
>> topTable(fit3, number=2, coef="mutant", adjust="fdr")
>> 
>> Here is my R session information.
>> 
>> R version 2.9.0 (2009-04-17)
>> i386-apple-darwin8.11.1
>> 
>> locale:
>> en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
>> 
>> attached base packages:
>> [1] stats     graphics  grDevices utils     datasets  methods   base
>> 
>> other attached packages:
>> [1] limma_2.18.0
>> 
>> Thank you very much for your help!
>> 
>> Best regards,
>> 
>> Julie
>> 
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