[BioC] cDNA microarray Questions

Naomi Altman naomi at stat.psu.edu
Tue Mar 2 05:26:59 MET 2004

Many people delete low quality genes based on either comparison between 
background and foreground, comparison between the mean and median 
foreground, or visual inspection.  I am reluctant to put a guess as to a 
good value for correlation based on the data I have worked with, which have 
been low-quality pilot studies with many spots deleted due to quality. 
However, it surely depends on the biological system - inbred lines in a 
highly controlled environment should be less variable, outbred and natural 
populations much more.  Also, the correlations that you see in the 
literature are generally after normalization - global normalization will 
not affect the correlation, but lowess (or loess) certainly will.  50% 
seems low compared to what I have heard - but then, I have mostly heard 
about model organisms under controlled conditions.


At 10:12 AM 3/1/2004, michael watson (IAH-C) wrote:
>As low as 0.5 for pearson and 0.8 for spearman
>But I'm not holding up my data as a shining example
>Surely if there is a lot of natural variation in the biological system, 
>then you're going to get large variation between biological replicates.
>-----Original Message-----
>From: Naomi Altman [mailto:naomi at stat.psu.edu]
>Sent: 28 February 2004 05:20
>To: michael watson (IAH-C); 'rwin qian'; bioconductor at stat.math.ethz.ch
>Subject: RE: [BioC] cDNA microarray Questions
>What do you mean by "very low"?
>At 04:24 AM 2/27/2004, michael watson (IAH-C) wrote:
> > >The correlation coefficients are very low. Is that the normal case?
> > >Do I need to delete some poor quality genes before any analysis and
> > >what rule should I use?
> >
> >Which correlation coefficient are you using?  I regularly see very low
> >pearson correlation coefficients between biological replicates but that
> >can be put down to natural biological variation - no two organisms are the
> >same, right?  BUT if you start seeing low correlations between technical
> >replicates (e.g. replicate samples from the same
> >animal/tissue/organ/whatever) then that indicates that you have a lot of
> >variation in your technology, which is bad.
> >
> >ON another note, I always find the Spearman Rank Correlation Coefficients
> >to be much higher.
> >
> >Mick
> >
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>Naomi S. Altman                                814-865-3791 (voice)
>Associate Professor
>Bioinformatics Consulting Center
>Dept. of Statistics                              814-863-7114 (fax)
>Penn State University                         814-865-1348 (Statistics)
>University Park, PA 16802-2111
>Bioconductor mailing list
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111

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