[BioC] Single slide analysis using Limma

[Sean Davis]

On 12/29/05 6:45 AM, "Ankit Pal" <pal_ankit2000 at yahoo.com> wrote:

> Hello,
>   Could anyone tell me how to go about doing an analysis for a single
> microarray slide using limma.

You can't is the short answer.  Limma employs a model that assumes
microarray replication is present.

>   Below is the code I used to specify the design,
>   
>   fit <- lmFit(MA, design=c(1))
>   
>   But I get the following errorr once I go to  fit <- eBayes(fit)
>   
>   Error in ebayes(fit = fit, proportion = proportion, stdev.coef.lim =
> stdev.coef.lim) :
>           No residual degrees of freedom in linear model fits
>   
>   I am not a statistician, so I need help to interpret the above error.

In this case, it means that you are trying to do a t-test with only one
sample--you can't. 

The simplest way to go about this is to rank the genes by fold-change
(two-channel data).  That is really the best you can do with only one slide.
Determining statistical significance is another question (and people have
tried to answer it), but I would argue that doing so really isn't that
meaningful and that if you really want to know what is "significant", you
need some replicates (the number of which depends on the experimental
conditions and design).

Hope that clarifies things a bit.
Sean