Hi James, I don't know how disperse your percent.present values are, but I don't think that this is the best quality metrics to rely on. I would suggest starting to look at the scale factor. Concerning these percent.present values, if you see large differences, you may start by separating the different groups you analyze, and check if the values are coherent inside these groups. To detect outliers, you may try to plot the percent.present values as a boxplot to get an idea of putative outliers. Have a look here [*] for an example. Laurent [*] http://www.dnavision.be/lgatto/yaqc.png If you are interested in generating such plots, let me know. I have a package that generates them. Laurent Gatto DNAVISION SA ________________________________________ From: James Anderson [mailto:janderson_net@yahoo.com] Sent: Tuesday, June 26, 2007 3:12 PM To: Laurent Gatto; bioconductor Subject: RE: [BioC] QC question using simpleaffy Laurent, Yeah, I figured this out later. They are different. So in terms of identifying outliers by percentage of present calls, would that be reasonable to just pick up those with lowest percentage of present calls? The manual says that the absolute value of percent.present is not a good metric, since some cells naturally express more genes than others, then is there any other way to take into consideration of this? Thanks, James Laurent Gatto <l.gatto at="" dnavision.be=""> wrote: Dear James, bioBCalls tells if the bioB probe (one hybridization control probe, AFFX-BioB-3_at or AFFX-r2-Ec-bioB-3_at depending on the array type) is present whereas is percent.present gives the percentage of all probe sets that are called present on the array. HTH, Laurent Laurent Gatto DNAVISION SA -----Original Message----- From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of James Anderson Sent: Monday, June 25, 2007 9:05 PM To: bioconductor Subject: [BioC] QC question using simpleaffy I read from the manual of QC using simpleaffy, the object obtained is called "qc", which I type slotNames (qc) [1] "scale.factors" "target" "percent.present" [4] "average.background" "minimum.background" "maximum.background" [7] "spikes" "qc.probes" "bioBCalls" I am trying to locate those arrays with some quality problem. when I type which(qc at bioBCalls == "A"), they are not fully consistent with the arrays with the lowest qc at percent.present. The manual says that the absolute value of percent.present is not a good metric, since some cells naturally express more genes than others. So what's the other information except percent.present that is used to determine whether an array is "A" or "P"? Many thanks, James --------------------------------- The fish are biting. [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor ________________________________________ Be a better Heartthrob. Get better relationship answers from someone who knows. Yahoo! Answers - Check it out.