[BioC] removal of genes with low expression values

Naomi Altman naomi at stat.psu.edu
Wed Jul 7 15:22:32 CEST 2010


Isn't filtering on spread like pretesting for 
differential expression?  Maybe not such a good idea.

When using MAS5, it is traditional to use the 
Affy presence/absence score.  (Not necessarily optimal ...)

--Naomi

At 06:53 AM 7/7/2010, Yuan Hao wrote:
>Usually it can be filtered based on IQR and/or variance across
>samples, which might be worthy of thinking besides 'average'
>
>Yuan
>
>On 7 Jul 2010, at 11:47, Sean Davis wrote:
>
>>On Wed, Jul 7, 2010 at 6:28 AM, Hernando 
>>Martínez <hernybiotec at gmail.com >wrote:
>>
>>>Hi, I need to remove genes with low expression values from a
>>>expression
>>>matrix. I would like to remove those with an average of expression
>>>values
>>>less than a certain cut-off. I was thinking in computing the
>>>average for
>>>each row, create a list with the gene names for which their average
>>>is less
>>>than the cut-off, and remove those genes from the initial matrix.
>>>However,
>>>I
>>>have a couple of doubts that maybe you can help me with. Is there any
>>>package or function that makes this easier? And, does anyone know
>>>which
>>>cut-off to use for data normalized with RMA and for data normalized
>>>with
>>>MAS5? Thanks,
>>>
>>Take a look at the genefilter package.  However, what you describe
>>can be
>>done easily with standard R.
>>
>>I don't think there is such a thing as a "standard" cutoff for
>>microarray
>>data.
>>
>>Sean
>>
>>         [[alternative HTML version deleted]]
>>
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111



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