[BioC] objective criterion for identification of outlying arrays by pca IN GENE ST1.0 CHIPS

[Richard Friedman]

Benilton, Vincent, and List:

	Will the extreme asymmetry of the NUSE plot compromise its utility in  
arrayMvout ?

Thanks and best wishes,
Rich


On Nov 4, 2011, at 11:24 AM, Benilton Carvalho wrote:

> oligo, as Richard already tried, does offer some affyPLM features
> (NUSE+RLE) for (but not only) ST arrays. At the probeset level,
> however, NUSE boxplots are very asymmetric and I believe this is
> associated to the control probesets (I need to make some time to check
> this and allow some filtering if this is the case).
>
> b
>
> On 4 November 2011 15:03, Vincent Carey <stvjc at channing.harvard.edu>  
> wrote:
>> On Fri, Nov 4, 2011 at 10:26 AM, Richard Friedman <
>> friedman at cancercenter.columbia.edu> wrote:
>>
>>>
>>> On Nov 2, 2011, at 10:16 AM, Vincent Carey wrote:
>>>
>>>  you can read about formally calibrated outlier assessment for  
>>> microarrays
>>>> in
>>>>
>>>> http://bioinformatics.**oxfordjournals.org/content/25/**1/48<http://bioinformatics.oxfordjournals.org/content/25/1/48 
>>>> >
>>>>
>>>
>>> Dear Vincent and List,
>>>
>>>        I read your paper with great interest. i will implement it  
>>> for
>>> datasets for Affymetrix Chips with
>>> mismatch probes, to which it is geared, along with the weighting  
>>> method
>>> suggested by Jim MacDonald, for arrays which pass the test.  
>>> However a Gene
>>> ST1.0 dataset has come up with this kind of rejection question.  
>>> Has you
>>> method be adapted to Gene ST1.0 arrays? If not, do you know of
>>> a method analogous to yours which can be used for ST1.0s.
>>>
>>
>> There is a fair amount of generality in arrayMvout but it has not  
>> all been
>> exercised to the same degree.  The simplest uses work from  
>> affyBatch or
>> lumiBatch instances and compute QA statistics tailored to the  
>> respective
>> platforms.  If you have a data frame of array-specific QA  
>> statistics for
>> some other platform, arrayOutliers() will perform calibrated  
>> multivariate
>> outlier detection with these measures.  For the early affy arrays,  
>> NUSE and
>> RLE statistics from affyPLM play a role; I don't know if these are  
>> readily
>> computed for 1.0 ST arrays at this time.  arrayMvout uses
>> Mahalanobis-distance based procedures, but the distance is  
>> robustified by
>> inward peeling to deal with masking problems that can arise with  
>> multiple
>> outliers.
>>
>> Let's not forget the  Bioconductor mdqc package, which also deals  
>> with a
>> differently robustified Mahalanobis distance for this purpose.
>>
>>
>>>
>>> Thanks and best wishes,
>>> Rich
>>> ------------------------------**-----------------------------
>>> Richard A. Friedman, PhD
>>> Associate Research Scientist,
>>> Biomedical Informatics Shared Resource
>>> Herbert Irving Comprehensive Cancer Center (HICCC)
>>> Lecturer,
>>> Department of Biomedical Informatics (DBMI)
>>> Educational Coordinator,
>>> Center for Computational Biology and Bioinformatics (C2B2)/
>>> National Center for Multiscale Analysis of Genomic Networks (MAGNet)
>>> Room 824
>>> Irving Cancer Research Center
>>> Columbia University
>>> 1130 St. Nicholas Ave
>>> New York, NY 10032
>>> (212)851-4765 (voice)
>>> friedman at cancercenter.**columbia.edu <friedman at cancercenter.columbia.edu 
>>> >
>>> http://cancercenter.columbia.**edu/~friedman/<http://cancercenter.columbia.edu/%7Efriedman/ 
>>> >
>>>
>>> I am a Bayesian. When I see a multiple-choice question on a test  
>>> and I
>>> don't
>>> know the answer I say "eeney-meaney-miney-moe".
>>>
>>> Rose Friedman, Age 14
>>>
>>>
>>>
>>>
>>>
>>>
>>>> On Wed, Nov 2, 2011 at 10:04 AM, Richard Friedman  
>>>> <friedman at cancercenter.
>>>> **columbia.edu <friedman at cancercenter.columbia.edu>> wrote:
>>>> Dear Bioconductor List,
>>>>
>>>>       Does anyone know of an objective criterion for the  
>>>> identification
>>>> of outlying arrays
>>>> by pca?
>>>>
>>>>       I usually do this subjectively. However the experimental
>>>> investigator whom I am helping
>>>> has a different subjective sense than I do, so that I wonder if  
>>>> there is
>>>> a hard-and-fast criterion.
>>>>
>>>>
>>>
>>>
>>> -
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>
>>        [[alternative HTML version deleted]]
>>
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