[BioC] import data for limma analysis

[Tineke Casneuf]

The problem is that I have a very large
dataset, with more than 50 experiments (so 300 datasets, since replicates
were used). I have written some scripts, so that calculating the averages and

ratios is easy and fast. If it would be better for my research however to
analyse the data with bioconductor (thereby I mean the functions
model.matrix, makeContrasts, contrasts.fit), I still can do that (it would
just take more time). I don't really understand what the 'advantage' is of
using the linear fit. I know what a linear fit is, but I understand how it is

done on microarray data, or what happens to the data.

If it's not needed I guess I can do this (please correct me if I'm wrong):
- import the data (genes horizontal and experiments vertical), with the names

of the genes as row names and the log ratios in the table:
> scan("list_of_genes", what = "list") -> genes
> read.table(file = "signals_in_table", row.names = genes) -> data

[- Instead of using the expressions in the limma tutorial:
> data <- ReadAffy()
> eset <- rma(data)]

[- So since I have already calculated the averages of the replicates and the
ratios between experiments and controls, I guess I can also skip these
commands:
> design <- model.matrix(~ -1+factor(c(1,1,1,2,2,3,3,3)))
> colnames(design) <- c("group1", "group2", "group3")
> contrast.matrix <- makeContrasts(group2-group1, group3-group3,
group3-group1, levels=design)]
> fit <- lmFit(data, design)
> fit2 <- contrasts.fit(fit, contrast.matrix)]

- To find the differential expressed genes, can I just perform this function
on my data?
> fit2 <- eBayes(data)


Tineke

--
==================================================================
Tineke Casneuf          Tel: 32 (0)9 3313692
DEPARTMENT OF PLANT SYSTEMS BIOLOGY           Fax:32 (0)9 3313809
GHENT UNIVERSITY/VIB,    Technology Park 927, B-9052 Gent, Belgium
Vlaams Interuniversitair Instituut voor Biotechnologie         VIB
e-mail:ticas at psb.ugent.be     http://www.psb.ugent.be/bioinformatics/