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@stat.math.ethz.ch > [mailto:bioconductor-bounces@stat.math.ethz.ch]On Behalf Of > Naomi Altman > Sent: 28 February 2004 03:57 > To: Francois Collin; Lawrence Paul Petalidis; > bioconductor@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@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@stat.math.ethz.ch > > > > >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor > > > >_______________________________________________ > >Bioconductor mailing list > >Bioconductor@stat.math.ethz.ch > >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor > > 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 > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor >