[BioC] AffyPLM

Naomi Altman naomi at stat.psu.edu
Sat Feb 28 03:56:55 MET 2004

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.


At 09:31 AM 2/19/2004, Francois Collin wrote:
>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.
>--- 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
> >
> > _______________________________________________
> > Bioconductor mailing list
> > Bioconductor at stat.math.ethz.ch
> >
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>Bioconductor at stat.math.ethz.ch

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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