Thank you so much Simon, now it's clearer to me.

Best Regards,

Avhena

On Thu, Feb 25, 2010 at 5:05 AM, Simon Anders <anders@embl.de> wrote:

> Hi
>
>
> avehna wrote:
>
>> I'm trying to identify genes that are differentially expressed in 4
>> different treatments vs Control. First, I applied
>> *pairwise.comparison*(simpleaffy library) to my data, and then, just
>> to compare both results, I
>> tried *lmFit* and *eBayes* (from limma library). I was wondering which
>> method is best, because although  pairwise.comparison applies a t-test, it
>> doesn't include Bonferroni correction. On the other hand I'm not sure
>> whether fitting the data to a linear model using lmFit and eBayes is more
>> convenient. I have also found another library(maanova) that uses Anova and
>> it's also suitable for DNA microarray analyzes.
>>
>
> First of all: If you have the trivial linear model of just comparing two
>  conditions against each other, the F test for the coefficient for the
> condition (i.e., the test that ANOVA does) is the same thing as a t test.
> Hence, doing a t test and an ANOVA should give the same results in the case
> of just two conditions.
>
> The main issue with the t test is that the denominator of the 't' value is
> the sample variance, as estimated from the values of the gene in the
> replicates. As you only have four replicates, this estimate may fluctuate a
> lot. What Limma's eBayes does is to "share information across genes", i.e.,
> it find a compromise between the variance estimate for the gene under
> consideration and the average variance from all the genes. This gives more
> reliable results.
>
> The correction for multiple testing is a completely separate issue: All
> these techniques give you raw p values which you should correct for multiple
> testing, either with the standard R function 'p.adjust' or with Storey's
> 'qvalue' package. Make sure you understand what this correction actually
> does, i.e., read up on family-wise error rate (FWER) and especially false
> discovery rate (FDR).
>
> Cheers
>  Simon
>
>
> +---
> | Dr. Simon Anders, Dipl.-Phys.
> | European Molecular Biology Laboratory (EMBL), Heidelberg
> | office phone +49-6221-387-8632
> | preferred (permanent) e-mail: sanders@fs.tum.de
>
>

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