Hi Naomi, Thank you for your help. > It looks to me as if there is a problem in this experiment. I cannot > speak for the efficacy of the RNA degradation plot. But unless a > large amount of differential expression occurs in this experiment, > the very close similarity between the duplicates compared to the > other conditions leads me to thing that these duplicates were either > not biological replicates, or the duplicates were processed together > causing correlation. I know that the replicates are biological replicates, so I think very likely that they processed the duplicates together ( will check with the experimenter) However, if this is the case, what we can do to? It violates the assumption of Limma ? Maybe Rank product can be a solution since it computes 4 ratios among duplicates from two conditions? Many thanks! fangxin > I have seen this type of thing with spotted arrays when arrays > processed in a single batch are much more similar than biological > replicates processed on different days. > > --Naomi > > At 08:12 AM 1/18/2006, James W. MacDonald wrote: >>fhong at salk.edu wrote: >> > Dear list, >> > >> > I have this 8 affy arrays under 2*2 factorial design, with duplicates >> > under each condition. The RNA degradation plot worries me since the >> slopes >> > from 8 arrays are so different, with duplicates under each condition >> as >> > one group (see the QC plots at http://cactus.salk.edu/temp/QC-1.jpeg) >> > I would suspect that these arrays were processed under different >> levels >> > if amplification. >> > >> > My problem is how to handle this data set beside doing the >> normalization? >> > Will this pattern seriously bias the result? I read some previous >> message >> > about this topic, just hope to get more information. >> >>I find that the RNA degradation plots are less useful for indicating >>possible problems than the density plots. If the density plots are all >>reasonably similar, in my experience the normalization should be fine. >>Another excellent plot for detecting problems is the residual plot in >>the affyPLM package. >> >> >>Best, >> >>Jim >> >> >> > >> > Many thanks! >> > Fangxin >> > >> > >> > -------------------- >> > Fangxin Hong Ph.D. >> > Plant Biology Laboratory >> > The Salk Institute >> > 10010 N. Torrey Pines Rd. >> > La Jolla, CA 92037 >> > E-mail: fhong at salk.edu >> > (Phone): 858-453-4100 ext 1105 >> > >> > >> > >> > -------------------- >> > Fangxin Hong Ph.D. >> > Plant Biology Laboratory >> > The Salk Institute >> > 10010 N. Torrey Pines Rd. >> > La Jolla, CA 92037 >> > E-mail: fhong at salk.edu >> > (Phone): 858-453-4100 ext 1105 >> > >> > _______________________________________________ >> > Bioconductor mailing list >> > Bioconductor at stat.math.ethz.ch >> > https://stat.ethz.ch/mailman/listinfo/bioconductor >> >> >>-- >>James W. MacDonald >>Affymetrix and cDNA Microarray Core >>University of Michigan Cancer Center >>1500 E. Medical Center Drive >>7410 CCGC >>Ann Arbor MI 48109 >>734-647-5623 >> >>_______________________________________________ >>Bioconductor mailing list >>Bioconductor at stat.math.ethz.ch >>https://stat.ethz.ch/mailman/listinfo/bioconductor > > Naomi S. Altman 814-865-3791 (voice) > Associate Professor > Dept. of Statistics 814-863-7114 (fax) > Penn State University 814-865-1348 (Statistics) > University Park, PA 16802-2111 > > > -------------------- Fangxin Hong Ph.D. Plant Biology Laboratory The Salk Institute 10010 N. Torrey Pines Rd. La Jolla, CA 92037 E-mail: fhong at salk.edu (Phone): 858-453-4100 ext 1105

fhong at salk.edu wrote: > Hi Jim, > Thank you for your useful input. > > >>I find that the RNA degradation plots are less useful for indicating >>possible problems than the density plots. > > Do you mean that "RNA degradation plots are less useful for indicating > possible problems" or the problems indicated by RNA degradation plots are > less profound than those from density plots? Both. In my experience, if I see a sample that has high background (shifted to the right) on the density plot, it is almost always going to require a re-fragmentation and re-hyb. For the vast majority of samples, this is sufficient to get reasonable results. On the other hand, different slopes on the degradation plot often don't show up as being a problem (on residual plots, PCA plots, etc). > > > >>If the density plots are all >>reasonably similar, in my experience the normalization should be fine. >>Another excellent plot for detecting problems is the residual plot in >>the affyPLM package. > > Two questions here, thanks. > (1) Is it true that as long as the normalization is fine (for example, the > boxplot and density plot after normalization are similar among arrays), we > would proceed for further analysis. Well, here is the problem. When you do a quantile normalization you will *always* end up with boxplots and density plots where the samples all look identical. That is pretty much what the normalization is supposed to do. The problem is whether or not it is a valid idea to use a quantile normalization for a particular data set (e.g., do the data meet the assumptions required to do a quantile normalization). > (2) I did check the residual plot using affyPLM, P=please visit: > http://cactus.salk.edu/temp/QC_t.doc > What does it tell me? Some defects on the array? There are some obvious defects on some of the arrays (my favorite being the 'window' on Stem_Base_1), but since the probes in each probeset are distributed all over the chip I don't think these will have a big effect. However, Stem_Top_2 has consistently large residuals, which indicates that the medianpolish fit does not explain these data very well. If we were running these chips in our core, this sample would almost certainly be redone. HTH, Jim > > Thank you very much for your kind help. > > Many thanks! > Fangxin -- James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623

Dear Fangxin, My feeling is that StemT2 has such a different distribution to the other chips that it should not be included in the analysis. It is a tricky question though because the shape of the density distribution of StemT2 looks more like the shape we expect in a good quality chip, but StemT2 has a very low intensity for an affy chip (compared to our chips). How much sample RNA are you using for each chip...could you have used less for StemT2 or could the hybridization have been not as good for StemT2? I was wondering if the Bioconductor community knew if there is any evidence/guide for how different a distribution has to be before the chips should not be normalized together? This is a question we come up against again and again (especially when analyzing published data sets). Regards Marg -----Original Message----- From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of fhong at salk.edu Sent: Thursday, 19 January 2006 4:45 AM To: James W. MacDonald Cc: bioconductor at stat.math.ethz.ch Subject: Re: [BioC] RNA degradation problem Hi Jim, Thank you for your useful input. > I find that the RNA degradation plots are less useful for indicating > possible problems than the density plots. Do you mean that "RNA degradation plots are less useful for indicating possible problems" or the problems indicated by RNA degradation plots are less profound than those from density plots? > If the density plots are all > reasonably similar, in my experience the normalization should be fine. > Another excellent plot for detecting problems is the residual plot in > the affyPLM package. Two questions here, thanks. (1) Is it true that as long as the normalization is fine (for example, the boxplot and density plot after normalization are similar among arrays), we would proceed for further analysis. (2) I did check the residual plot using affyPLM, P=please visit: http://cactus.salk.edu/temp/QC_t.doc What does it tell me? Some defects on the array? Thank you very much for your kind help. Many thanks! Fangxin > > Best, > > Jim > > >> >> Many thanks! >> Fangxin >> >> >> -------------------- >> Fangxin Hong Ph.D. >> Plant Biology Laboratory >> The Salk Institute >> 10010 N. Torrey Pines Rd. >> La Jolla, CA 92037 >> E-mail: fhong at salk.edu >> (Phone): 858-453-4100 ext 1105 >> >> >> >> -------------------- >> Fangxin Hong Ph.D. >> Plant Biology Laboratory >> The Salk Institute >> 10010 N. Torrey Pines Rd. >> La Jolla, CA 92037 >> E-mail: fhong at salk.edu >> (Phone): 858-453-4100 ext 1105 >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor > > > -- > James W. MacDonald > Affymetrix and cDNA Microarray Core > University of Michigan Cancer Center > 1500 E. Medical Center Drive > 7410 CCGC > Ann Arbor MI 48109 > 734-647-5623 > > -------------------- Fangxin Hong Ph.D. Plant Biology Laboratory The Salk Institute 10010 N. Torrey Pines Rd. La Jolla, CA 92037 E-mail: fhong at salk.edu (Phone): 858-453-4100 ext 1105 _______________________________________________ Bioconductor mailing list Bioconductor at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/bioconductor