also http://www.bioconductor.org/packages/2.11/bioc/vignettes/pcaMethods/inst/doc/pcaMethods.pdf<http://www.bioconductor.org/packages/2.11/bioc/vignettes/pcaMethods/inst/doc/pcaMethods.pdf>

if you are willing to simply truncate loadings at some arbitrary value (not
always the worst idea of all time mind you)

superPC and the preconditioned lasso turn this strategy into a method for
obtaining sparse classifiers, FWIW.


On Mon, May 7, 2012 at 10:46 AM, Tim Triche, Jr. <tim.triche@gmail.com>wrote:

> try using the 'sparcl' package or something like this:
> http://www.biomedcentral.com/1471-2105/11/296
>
> the point is to threshold vigorously enough that most of the loadings are
> forced to zero
>
>
>
> On Mon, May 7, 2012 at 10:16 AM, Kripa R <kripa777@hotmail.com> wrote:
>
>>
>> Maybe this is very basic, but how do you identify those 500 genes for the
>> heatmap?
>>
>> .kripa
>>
>> From: amackey@virginia.edu
>> Date: Mon, 7 May 2012 11:47:16 -0400
>> Subject: Re: [BioC] LIMMA: plotMDS
>> To: kripa777@hotmail.com
>> CC: bioconductor@r-project.org
>>
>> All genes contribute to all principle components; some just more than
>> others.  I've found it useful (or perhaps just entertaining) to see
>> heatmaps of the first N (say 10) component loadings, constrained to the 500
>> genes whose variances contribute most to those components.
>>
>>
>> -Aaron
>>
>> On Sun, May 6, 2012 at 7:21 PM, Kripa R <kripa777@hotmail.com> wrote:
>>
>>
>>
>>
>> Hi I was wondering how I can figure out which genes correspond to each of
>> the principle components ($cmdscale.out). Gene.selection is set to pairwise
>> for the top 500 but I'd like to know exactly which genes are being
>> considered for cmdscale.out[,3], for example.
>>
>>
>>
>>
>>
>> Thanks for the help!
>>
>>
>>
>> .kripa
>>
>>        [[alternative HTML version deleted]]
>>
>>
>>
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>
>
>
> --
> *A model is a lie that helps you see the truth.*
> *
> *
> Howard Skipper<http://cancerres.aacrjournals.org/content/31/9/1173.full.pdf>
>
>


-- 
*A model is a lie that helps you see the truth.*
*
*
Howard Skipper<http://cancerres.aacrjournals.org/content/31/9/1173.full.pdf>

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