[BioC] HT qPCR - error in scale rank invariant

[Heidi Dvinge]

Dear Andreia,

> Dear all,
>
> I am analysing qPCR data from the Exiqon where I have one card per sample,
> in each card I have one observation for each miRNA. I have in total 8
> cards,
> 2 for treatment 1, 3 for treatment 2 and 3 for treatment 3. Each card has
> one endogenous gene, which I wouldn't like to use to normalize Ct values
> because is being affected by the type of treatment. So I would like to use
> scale.rank.
> I am getting the following error:
>
> sr.norm <- normalizeCtData(raw.cat, norm = "scale.rank")
> Error in smooth.spline(ref[i.set], data[i.set]) :
>   need at least four unique 'x' values
>
It sounds like there aren't enough rank-invariant genes across your 8
cards. If that's the case, then this is admittedly not the most useful
error message, and it should be changed. What does it say when you run
traceback() following the error?

The parameter "scale.rank.samples" in normalizeCtData() will let you set
how many of the samples each gene has to be rank-invariant across in order
to be excluded. Per default this is the number of samples-1. You can try
lowering that number, although keeping in mind that the lower it is, the
less robust your resulting rank-invariant genes are. If your samples are
all highly variable across all genes, it might not be possible for you to
use this normalisation method.

If this does not seem to be the problem, something else might be going on
with the function. In that case, please report back here and I can perhaps
have a look at your data.

I have been considering adding an additional parameter to normalizeCtData,
so that genes just have to be rank-invariant within a certain interval,
e.g. be located within -/+5 of each other on the ranked list. For rather
low-throughput qPCR cards that could mess things up though.

HTH
\Heidi

> Does this mean I don't have enough replicates?
>
> thanks for the help
>
> Andreia
>
> --
> --------------------------------------------
> Andreia J. Amaral
> Unidade de Imunologia Clínica
> Instituto de Medicina Molecular
> Universidade de Lisboa
> email: andreiaamaral at fm.ul.pt
>           andreia.fonseca at gmail.com
>
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