[BioC] Single slide analysis using Limma

[Naomi Altman]

A basic principle of statistical analysis of differential expression 
is to compare differences between conditions to differences among 
replicates within condition.
If you have no replication, you cannot use a statistical method such 
as LIMMA, MAANOVA, t-tests, Wilcoxon test or SAM.

All you can do is order the differences (M) from largest to smallest, 
but this does not tell you anything about statistical significance.

--Naomi

At 06:45 AM 12/29/2005, Ankit Pal wrote:
>Hello,
>   Could anyone tell me how to go about doing an analysis for a 
> single microarray slide using limma.
>   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.
>
>   Thanks and regards
>
>   Ankit
>
>
>
>
>
>---------------------------------
>
>
>         [[alternative HTML version deleted]]
>
>_______________________________________________
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch
>https://stat.ethz.ch/mailman/listinfo/bioconductor

Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111