[BioC] pre-processing Agilent data to remove a bad sample

[Stephen Rudd]

Dear bioconductor colleagues

I am fighting with a support project using two colour Agilent arrays. As
expected with the typical academic microarray study, there are too many time
points and not enough replicates.

Within the problem study I have 19 arrays, containing 38 samples. The data looks
pretty good throughout but a single sample is a dramatic outlier within
correspondence analysis and clustering. I therefore wish to remove this sample
from the analysis (but I don't have much experience with Agilent).

Data has been built into an marrayRaw object, and I have removed the sample from
the object, but the loess normalisation will not proceed; I suspect that paired
data is required?

My question is therefore how could (should) I remove this data point
representing the signal from one channel of an array. This data should be
removed earlier within the analysis because there are some rather subtle DEG
effects later on in the time series. I don't wish to remove the whole array
since the paired data is of considerable value (through lack of replicates!).
Would it make more sense to remove this data channel from the result marrayNorm
object (the first normalisation is within array).

Any comments, suggestions or otherwise would be gratefully received

Thanks

Stephen

--
Dr Stephen Rudd
Adjunct professor of plant genomics
Senior specialist, bioinformatics
A schizophrenic coexistence between pharma and academia