Dear Joern, your guess was right. It was an issue with my probeAnno object. I created the probeAnno this way: (reads is an AlignedRead object with all my probes) pos = data.frame(CHROMOSOME=chromosome(reads), PROBE_ID=as.character(id(reads)), POSITION=position(reads), LENGTH=width(reads)) probeAnno = posToProbeAnno(pos, genome="Mus_musculus.NCBIM37.55", microarrayPlatform="mm.prompr.v02") Adding the parameter stringsAsFactors=FALSE to the data.frame() function solved my problem. Without that parameter the "X.index" in my probeAnno were factors. Thanks, Hans-Ulrich Joern Toedling wrote: > Dear Hans-Ulrich, > > in that case, I am afraid I cannot immediately tell you what the source of the > problem is. You are right, the smoothed probe intensities of these probes > should all be greater than y0. And in my analyses, I have never observed > something else. > How do the ChIP-enriched region look like when you plot them? > (for example via > plot(chers[[1]], eSetS, probeAnno) > ). If these plots indicate correct results than at least the positions of your > enriched regions seem to be correct and the problem is with assigning the > probe identifiers to the enriched regions. > There might be an issue with your probeAnno object and the way you generate it. > What is the result of > probeAnno["1.index"][probeAnno["1.start"]>=10001787 & > probeAnno["1.start"]<=0002329] > ? These probe identifiers should include the ones in the first enriched region. > I would suggest to use different probe names than "as.character" of the row > numbers. Due to R's implicit conversion between vector formats, such names > could lead to all sorts of hard-to-debug problems. > If you provide me with a short excerpt of your data and the example script, I > could have a deeper look into it to see where the problem might be. > > Best regards, > Joern > > On Tue, 20 Oct 2009 21:10:20 +0200, Hans-Ulrich Klein wrote > >> Dear Joern, >> >> the feature names of my ExpressionSet instance are: >> >> > all(featureNames(eSetS) == as.character(1:nrow(eSetS))) >> [1] TRUE >> >> So in my case both expressions >> > exprs(eSetS)[as.numeric(chers[[1]]@probes),] >> and >> > exprs(eSetS)[chers[[1]]@probes,] >> return the same probes that have log ratios smaller than y0 as >> described below. >> >> Best wishes, >> Hans-Ulrich >> >> Joern Toedling wrote: >> >>> Hello, >>> >>> I suspect that there is some issue with converting vectors between different >>> formats and the identifiers of your probes (the 'featureNames' of the >>> ExpressionSet) here. >>> The actual way to obtain those intensities with version 1.8.0 should be >>> >>> exprs(eSetS)[as.numeric(chers[[1]]@probes),] >>> >>> Please let me know if this does not give the expected results. >>> >>> However, I admit that providing indices as a character vector for the probes >>> slot was not necessary and rather misleading. Thus I have made slight changes >>> to the function and provided an additional method 'probes' which allows you to >>> obtain a character vector of probe names from each ChIP-enriched region >>> without having to access any slots directly. >>> >>> These changes can be found in the current development version 1.9.15, which >>> you can obtain from the Bioconductor repository tomorrow, and will also be in >>> the new release version (Ringo 1.10.0) at the end of this month. >>> >>> With the new version, the following is the preferred way for obtaining the >>> > values: > >>> exprs(eSetS)[probes(chers[[1]]),] >>> >>> Hope this helps. >>> >>> Best regards, >>> Joern >>> >>> On Mon, 19 Oct 2009 12:05:03 +0200, Hans-Ulrich Klein wrote >>> >>> >>>> Hello, >>>> >>>> I am confused about the results returned from the >>>> "findChersOnSmoothed" function in the Ringo package. I have an >>>> ExpressionSet object storing normalized log ratios (ChIP / Control) >>>> from three replicates. I use this analysis workflow: >>>> >>>> > eSetS = computeRunningMedians(eSet, probeAnno, modColumn="type", >>>> winHalfSize=400, min.probes=5, >>>> combineReplicates=TRUE) >>>> [...] >>>> > y0 = upperBoundNull(exprs(eSetS), prob=0.99) >>>> > chers = findChersOnSmoothed(eSetS, probeAnno, thresholds=y0, >>>> distCutOff=600, minProbesInRow=3) >>>> >>>> Surprisingly, the first enriched region does not contain any probe >>>> intensity above the threshold y0. This applies to many regions >>>> called enriched. >>>> >>>> > chers[[1]] >>>> BCR_ABL.chr1.cher1 >>>> Chr 1 : 10001787 - 10002329 >>>> Antibody : BCR_ABL >>>> Maximum level = 1.665789 >>>> Score = 9.486747 >>>> Spans 15 probes. >>>> > y0 >>>> [1] 0.7279903 >>>> > dim(eSetS) >>>> Features Samples >>>> 4212009 1 >>>> > exprs(eSetS[chers[[1]]@probes,]) >>>> BCR_ABL >>>> 112645 0.2140274 >>>> 112646 0.2469170 >>>> 112647 0.2485301 >>>> 112648 0.2501433 >>>> 112649 0.2765225 >>>> 112650 0.2813286 >>>> 112651 0.2803291 >>>> 112652 0.2727159 >>>> 112653 0.2469170 >>>> 112654 0.2469170 >>>> 112655 0.1166212 >>>> 112656 0.2355814 >>>> 112657 0.2355814 >>>> 112658 0.1608379 >>>> 112659 0.2063285 >>>> >>>> Did I check the correct probes? Should not be the intensities > 0.727? >>>> >>>> My Ringo version is 1.8.0. >>>> >>>> Thanks in advance, >>>> Hans-Ulrich >>>> > > > -- Hans-Ulrich Klein Department of Medical Informatics and Biomathematics University of M?nster Domagkstrasse 9 48149 M?nster, Germany Tel.: +49 (0)251 83-58405