[R] Can someone recommend a package for SNP cluster analysis of Fluidigm microarrays?

[R. Michael Weylandt]

I do think this is more of a Bioconductor question -- but no worries,
they're all much nicer there than we are here and won't flame you if
you double post :-)

Best,
Michael

On Thu, Jun 14, 2012 at 12:37 PM, Hans Thompson
<hans.thompson1 at gmail.com> wrote:
> I know that there are quite a few packages out that there for cluster
> analysis.  The problem that I am facing is finding a package that will not
> incorporate all my samples into clusters but just the samples that fit a
> threshold (that I have not set yet and may need help finding the right
> level) for genotyping. It should be able to "no call" samples outside the
> clusters. It also needs to accommodate a negative control sample by not
> including it in any genotype cluster.
>
> I'm looking at both nuclear and mitochondrial DNA so hopefully it can be
> sophisticated enough to set the number of cluster between two or three
> within the array.
>
> These genotyping arrays are either 48 samples x 48 assays, 96x96, or 192x24
> and it would be nice if it could accommodate any range of samples and
> assays.
>
> the data headings from the csv are:
>
> ID,Assay,Allele Y,Allele X,Name,Type,Auto,Confidence,Final,Converted,Allele
> Y,Allele X
>
> where Allele Y and Allele X are the plotted values and the vectors within
> the data.frame are 9216 (96x96) long.
>
> So what would be the recommended package for moving to a more quantifiable
> method of genotyping using cluster analysis?
>
> Thanks again.  Forgive me if this is a better question for bioconductor.  I
> will provide any additional context that I might have forgot to add here
> that could help.
>
>        [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.