Dear list,

I'm having some difficulties in using HTqPCR to analyze qPCR data obtained using the Biomark Fluidigm 96.96 array.

With the Fluidigm chips, one can measure expression of 96 genes in 96 samples on one plate, i.e. 9216 PCRs per plate (see http://www.fluidigm.com/products/biomark-chips.html for details).

In my experiment, I use 9 such plates. On each plate I have 88 different experimental samples, with different samples on each plate, totalling 792 unique experimental samples (associated with specific experimental conditions). On each plate, I also have 8 standard samples that are the same across all plates (1 NTC, 1 cDNA mix +RT, 1 cDNA mix -RT, 5 samples of a dilution series). 


I use 32 different genes (features), each replicated 3 times, in the same order on each plate.

Each original data file (as exported by the FLuidigm software) has data on one plate, i.e. 9216 rows with one PCR per row, with columns for sample name, feature name, Ct, quality calls, etc.
I managed to read in the 9 data files (from 9 plates) into one qPCRset object:
An object of class "qPCRset"
Size:  96 features, 864 samples
Feature types:           Reference, Test 
Feature names:           1.BGRP 1.BGRP 1.BGRP ...
Feature classes:          
Feature categories:      OK, Undetermined 
Sample names:            A1.1h A1.6a A1.11h ...

Is this a good way to structure my data? Or would it be better to create 9 qPCRset objects (1 for each plate)? Before spending more effort continuing this approach I'd appreciate your opinion on whether this is the way forward.


Among other things, I would like to do the following:
1. Check for spatial effects. When I use plotCtCard, it only plots one sample at a time, even though I have 96 samples on each plate. Is it possible to plot my 96 samples x 96 features? How can I specify this kind of layout?
2. Control for plate-specific effects. I have the same 8 standard samples on each plate (for all genes), and would like to use these repeated measurements to 'normalize' all other data across plates. However, I'm having a hard time even accessing and plotting the data.
3. Speficiy technical replicates. Each sample has been run on 32 genes in triplicate. Each feature name is represented 3 times (once for each technical rep). How can I specify that my 96 features are grouped per 3?
4.  Add information about my experimental design. My 792 experimental samples were obtained in a full factorial design with several biological replicates per treatment. Is it possible to add extra data to my qPCR set object? E.g. a matrix containing, per sample, information on sample name, value for factor 1, value for factor 2, etc.?

I do understand that this package was not developed specifically for dealing with data from these Fluidigm chips, but I haven't found any such package and as far as I know HTqPCR is the best package around for analysis of high-throughput qPCR data.

I hope someone can help me out a little bit. I'm new to R, but I'm not asking you to do my work for me, just some directions to help me do it myself. Thanks!

Cheers,
Vicencio


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