[BioC] Nanostring ncounterdata - DESeq

Vanessa Vermeirssen vanessa.vermeirssen at psb.vib-ugent.be
Mon Jul 25 13:33:45 CEST 2011

Dear all,

I need to statistically analyse Nanostring ncounter data to see if there
is differential expression between experiment and control. I have 3
biological replicates of each and the experimental set-up would slightly
favor a "_paired_" statistical approach.

Nanostring nCounter data are mRNA counts, like RNA-Seq, but I wonder if
they have the same properties like RNASeq data  i.e. I do only have the 
counts for 110
specifically selected genes. The deeper sampling of one sample compared 
to another e.g. is less
The manufacturer suggested some preprocessing of the data: scaling
against positive spike-ins, substracting background (and absent/present 
call generation).
In addition, we performed a normalization with 4 household genes 
(selected out of the 8
included in the 110 genes).

I did the DESeq package analysis using these preprocessed data, is this
package also appropriate in this case (e.g. the library normalization
step?)? Is the preprocessing correct for this?

In addition, I also did a t-test (paired and normal, equal variance,
which I tested, on the log2 data), because this has been described in
literature before.
Another paper describes an FDR permutation approach, but they don't seem
to have any biological replicates, but 32 control experiments and 10
control genes (Amit et al., 2009).
I also tried to do this on our data.

We have some nice "trends" in our data, which we kind of expected, but
the most significance is obtained with DESeq.

Could you advise me if DESeq is the most correct approach in our case?
What about the other statistical approaches I have tried?

A minor question relates to the preprocessing. How should I deal with 
absent/present calls obtained after the preprocessing in the course of 
statistical analysis?
Should I include them as NAs from the beginning, or re-evaluate the 
results at the end?

Thank you so much in advance already.

Best regards,
Vanessa Vermeirssen

Vanessa Vermeirssen, PhD

Tel:+32 (0)9 331 38 10                         Fax:+32 (0)9 3313809

Bioinformatics and Systems Biology
VIB Department of Plant Systems Biology, Ghent University
Technologiepark 927, 9052 Gent, BELGIUM

vamei at psb.vib-ugent.be           http://bioinformatics.psb.ugent.be/

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