[BioC] Taqman array analysis

[James Perkins]

Hi,


Apologies for the long list of questions, I have searched the mailing 
list but can't find much info about these arrays.


I am looking at low density PCR cards. They measure the expression 
levels of 96 different transcripts from a very small sample of human or 
animal tissue. There are actually 384 reactions going on but in our case 
each is done in quadruplicate (can be through biological or technical 
repetition).

I wondered if there was a favoured way to normalise this data. The most 
cited paper I have found is the Vandesompele 2002 paper using the 
geometric mean of a number of control genes, implemented in R in the SLqPCR.

Has anything else been developed that could be used with these cards? I 
guess quantile normalisation is out of the question since this makes 
some assumption that the majority of genes don't change in expression.

In addition, does anything exist in bioconductor (or outside it) to 
identify and remove outlying data points? The cards work by having a 
series of microfluidic channels deliver samples to 384 well PCR 
reactions. Sometimes an air bubble or something else means that the odd 
reaction fails.

Also is there a favoured way to determine what is consistently different 
between control and experimental samples. I assume a False Discovery 
Rate method is still in favour, possibly from t-test (or LIMMA??) but we 
are also interested in fold-change. Currently I just mean each gene and 
divide case by control to get a crude measure of fold change.

Kind regards,

James Perkins