[BioC] AffyPLM

[Arne.Muller at aventis.com]

If the horizontal striping (due to the scanner) is a systematic error, then
one doesn't have to bother, right? However, I've found some strange blobs
(with "tentacles") on a few of my chips that sneeked through the standard QC.
I guess this is not be a systematic error.

How do you decide when you've to discard a chip?

	regards,

	Arne


> -----Original Message-----
> From: bioconductor-bounces at stat.math.ethz.ch
> [mailto:bioconductor-bounces at stat.math.ethz.ch]On Behalf Of 
> Naomi Altman
> Sent: 28 February 2004 03:57
> To: Francois Collin; Lawrence Paul Petalidis;
> bioconductor at stat.math.ethz.ch
> Subject: Re: [BioC] AffyPLM
> 
> 
> Because the methods for combining the probes into gene 
> expression values 
> are robust to outliers, and because the probes are printed so 
> that probes 
> from the same genes are spatially dispersed, scratches and 
> small "blobs" 
> should not have much effect on your results.  Defects that 
> cover a large 
> percentage of your array will certainly be poor.  I have 
> looked at about 50 
> array images (mostly arabidopsis and mouse) and all have horizontal 
> striping that appears to be a scanner artifact.
> 
> --Naomi
> 
> At 09:31 AM 2/19/2004, Francois Collin wrote:
> >Paul,
> >The weights are derived from the model fit residuals -
> >they are transformations of the residuals standardized
> >by the model fit residual variance (fit here being
> >probe set specific).  Weights will be 1.0 if the
> >residuals are small compared to the residual variance,
> >and then decrease toward zero as the value of the
> >absolute standardized residuals increase.  On the chip
> >speudo-image of the weights, what is highlighted is
> >the spatial distribution of probes with large absolute
> >standardized residuals - outliers, in a sense, that
> >might have an impact on the fit, although this impact
> >is minimized by the robustness of the fit.  If there
> >is a local artifact - a scratch, uneven hybridization,
> >incomplete wash, bubble, etc - this will appear as a
> >cluster on the chip weight pseudo-image.  You could
> >also see a chip where residuals are uniformly elevated
> >throughout the chip  indicating that either the RNA
> >preparation, or the hybridization assay failed.
> >
> >The pseudo images of the residuals are just images of
> >untransformed residuals.  Here you may see local
> >clusters that do not appear in the weights -
> >corresponding to slightly dim or slightly bright spots
> >which lead to elevated residuals, but not elevated
> >enough to be picked up by the weights.  These are
> >useful to detect effects which may be good to know but
> >are too subtle to be picked up in the weights.  In
> >general, the images of the residuals tell the same
> >story as the weights.
> >
> >-francois
> >
> >
> >--- Lawrence Paul Petalidis <lpp22 at cam.ac.uk> wrote:
> > > Hello All,
> > > I am quite new to BioC and would appreciate your
> > > help on this. I am
> > > experimenting with AffyPLM and taking a look the
> > > post AffyPLM quality
> > > diagnostic pseudo-chip images [pset <- fitPLM(eset)
> > > and then
> > > image(pset)   ].  Can anybody recommend how one
> > > shoud interpret these
> > > images as a quality-checking step? Further, could
> > > one clarify for me
> > > what the differences between the plots that show
> > > weight, and those that
> > > show residuals?
> > > I thank you for your kind attention, Lawrence
> > >
> > >
> > >
> > > ___________________________________
> > > Lawrence-Paul Petalidis
> > > University of Cambridge
> > > Department of Pathology
> > > Division of Molecular Histopathology
> > > Addenbrookes Hospital, Level 3, Lab Block
> > > Hills Road, CB2 2QQ
> > > Cambridge
> > >
> > > Tel. : ++44 1223 762084
> > > Fax : ++44 1223 586670
> > >
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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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