[BioC] Classification

[Moshe Olshansky]

If you have just 5 genes and a decent number of samples you can use any of
the "conventional" (i.e. not high throughput) methods like LDA, trees,
Random Forest, SVM, etc.

> I will have a look at both packages. It's pcr data by the way
> thanks
>
> On 06/23/2011 05:56 PM, Tim Triche, Jr. wrote:
>> or CMA, which is perhaps a more systematic approach for classification.
>>   (the package name stands for Classification of MicroArrays)  Very well
>> thought out.
>>
>>
>> On Thu, Jun 23, 2011 at 8:02 AM, Sean Davis<sdavis2 at mail.nih.gov>
>> wrote:
>>
>>> On Thu, Jun 23, 2011 at 10:58 AM, David martin<vilanew at gmail.com>
>>> wrote:
>>>> Hi,
>>>> I have 5 genes of interest. I would like to know which combination(s)
>>>> of
>>>> genes gives the best disease separation. Which test could i use in my
>>>> training set to see which combination is the best classificer between
>>>> my
>>>> disease and my healthy population.
>>>>
>>>> Thanks for any comment or test that could be useful to answer that
>>> question.
>>>
>>> Check out the MLInterfaces package.  It should give you some ideas on
>>> where to start.
>>>
>>> Sean
>>>
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>>
>>
>>
>
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