[BioC] Combining data from runs

[Wolfgang Huber]

Hi Supriya,

if the aim is to analyse the data together, I would try the following:
- run rma on all 82 arrays together
- produce a quality report using the arrayQualityMetrics package 
(preferably with the current "devel" version) and check the diagnostics, 
in particular the heatmap, for how bad the batch effect really is.
- if there is no strong confounding between your two batches and the 
biological factor of interest, find differentially expressed genes using 
limma, keeping the batch as a covariate to absorb the (average) batch 
effect.
- for the hits, go back to the raw data (e.g. via scatterplot or 
heatmap) to double-check that there are no batch-related artifacts.

This seems to be an instance of where lazy experimental design has to be 
compensated by a more difficult data analysis, and you might want to 
have a word with whoever designed this experiment about that.

	best wishes
	Wolfgang


On Sep/10/10 10:53 PM, Supriya Munshaw wrote:
> We're using Affymetrix HG-U133_Plus_2 arrays and our experiment was done so that 8 of our samples were run initially as a test run, followed by running the remaining 74 samples. Since these were two different runs, I'm pre-processing them differently i.e. running rma on them separately. Is there a way to combine the two datasets after their probe level intensities have been normalized within each run since I want to include the initial 8 samples for differential gene expression analysis? If not, what is the best way to include the 8?
> Please let me know.
> Thanks!
>
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-- 


Wolfgang Huber
EMBL
http://www.embl.de/research/units/genome_biology/huber