[BioC] microarray outlier detection

[Peter Langfelder]

First, you should only remove outliers if there's a clear indication
you actually do have outliers, and the outliers are technical, not
biological. Especially if you have a small data set, removing any
samples can be counterproductive.

Should you nevertheless want to go ahead and remove some of the
samples, you may want to look at the SampleNetwork approach detailed
at

http://labs.genetics.ucla.edu/horvath/htdocs/CoexpressionNetwork/SampleNetwork/

The web site contains the necessary R code and a detailed tutorial on
how to use the function.

HTH,

Peter

On Fri, Aug 30, 2013 at 1:32 PM, guest [guest] <guest at bioconductor.org> wrote:
>
> Dear users,
>
> I have human gene 2.0 st array, total 12 samples including 4 groups, each group has 3 replicates. The lab person would like to remove one from each of the group due to the outliers, but from PCA plot, the samples are not clustered, it is hard to remove any sample as an outlier. I wonder if we have the package or function to solve the outlier detection issue on microarray.
>
> Thanks,
>
>
>  -- output of sessionInfo():
>
>> sessionInfo()
> R version 3.0.1 (2013-05-16)
> Platform: x86_64-apple-darwin10.8.0 (64-bit)
>
> locale:
> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
>
> attached base packages:
> [1] parallel  stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
>  [1] pd.hugene.2.0.st_3.8.0                oligo_1.24.1                          oligoClasses_1.22.0                   hugene20sttranscriptcluster.db_2.12.1
>  [5] org.Hs.eg.db_2.9.0                    RSQLite_0.11.4                        DBI_0.2-7                             AnnotationDbi_1.22.6
>  [9] Biobase_2.20.1                        BiocGenerics_0.6.0                    limma_3.16.6
>
> loaded via a namespace (and not attached):
>  [1] affxparser_1.32.3     affyio_1.28.0         BiocInstaller_1.10.3  Biostrings_2.28.0     bit_1.1-10            codetools_0.2-8
>  [7] ff_2.2-11             foreach_1.4.1         GenomicRanges_1.12.4  IRanges_1.18.2        iterators_1.0.6       preprocessCore_1.22.0
> [13] splines_3.0.1         stats4_3.0.1          zlibbioc_1.6.0
>
> --
> Sent via the guest posting facility at bioconductor.org.
>
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