Missing Autocorrelation in Ringo
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@torsten-waldminghaus-3502
Last seen 10.3 years ago
Dear all, I started using the Ringo package to analyze ChIP on Chip data and tried to make a nice plot of my nice autocorrelation. However, the plot shows no autocorrelation of neighbouring probes. This is unlikely to be because of the bad data, because I see really nice peaks when I plot signals on the chromosomal position and it fits very well with published data. If anybody has a suggestion what could be wrong or how I could find out what's wrong I would be happy. This is what I do in more detail: > RG <- read.maimages(files,"agilent")#read in array data I wrote an annotation file which looks like this ("POSITIONS" and "PROBE_ID" come from the RG file above): > annotationFile[1:3,] CHROMOSOME PROBE_ID POSITION LENGTH 1 1 2 218268 60 2 1 3 2239049 60 3 1 6 3448934 60 This I used to make a probeAnno object like this: > annoObject<-posToProbeAnno (annotationFile) Than I calculate autocorrelation: > exAc<-autocor(RG,probeAnno=annoObject, chrom="1",lag.max=1000) And plot: > plot(exAc) Thanks for any help, Torsten Torsten Waldminghaus Department of Cell Biology Institute for Cancer Research Rikshospitalet-Radiumhospitalet-HF Ullernchaussen 70 0310 Oslo tel: 47-22935973 fax: 47-22934580 e-mail: Torsten.Waldminghaus@rr-research.no http://openwetware.org/wiki/User:Torsten_Waldminghaus [[alternative HTML version deleted]]
Annotation Cancer Ringo Annotation Cancer Ringo • 1.5k views
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@joern-toedling-3465
Last seen 10.3 years ago
Hello, to clarify, do you mean that the plot does not show anything or that the plot indicates that there is no correlation? Is there an error message or warning? If so, what does it say? Further questions that could help me to figure out what is going on. What is the result of str(exAc) ls(annoObject) head(annoObject["1.start"]) Note that if your Agilent ChIP-chip files follow their convention to encode the probe position in a colum called "SystematicName" then you can also use the function "extractProbeAnno" on the RGList to obtain a probeAnno object. Last but not least, what is the output of sessionInfo()? Please always specify that when posting a question on the Bioconductor mailing list so that we can figure out if there might be problem with the package versions. Best regards, Joern0 On Mon, 29 Jun 2009 14:17:00 +0200, Torsten Waldminghaus wrote > Dear all, > > I started using the Ringo package to analyze ChIP on Chip data and tried > to make a nice plot of my nice autocorrelation. However, the plot shows > no autocorrelation of neighbouring probes. This is unlikely to be > because of the bad data, because I see really nice peaks when I plot > signals on the chromosomal position and it fits very well with published > data. If anybody has a suggestion what could be wrong or how I could > find out what's wrong I would be happy. > > This is what I do in more detail: > > > RG <- read.maimages(files,"agilent")#read in array data > > I wrote an annotation file which looks like this ("POSITIONS" and > "PROBE_ID" come from the RG file above): > > > annotationFile[1:3,] > > CHROMOSOME PROBE_ID POSITION LENGTH > > 1 1 2 218268 60 > > 2 1 3 2239049 60 > > 3 1 6 3448934 60 > > This I used to make a probeAnno object like this: > > > annoObject<-posToProbeAnno (annotationFile) > > Than I calculate autocorrelation: > > > exAc<-autocor(RG,probeAnno=annoObject, chrom="1",lag.max=1000) > > And plot: > > > plot(exAc) > > Thanks for any help, > > Torsten
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Hi, thanks for the answer and sorry for not making it more clear. I get a plot but it suggests that there is no autocorrelation. This means the column at point "0" is at 1.0 as usual but at "100", "200",... there are only dots which vary a bit in their size. Now the results you were interested in: > str(exAc) Class 'autocor.result' atomic [1:11] 1.00000 -0.00469 -0.00660 0.00538 0.00652 ... ..- attr(*, "chromosome")= chr "1" > ls(annoObject) [1] "1.end" "1.index" "1.start" "1.unique" > head(annoObject["1.start"]) [1] 68 154 189 294 365 440 I tried the function extractProbeAnno but it does actually not seem to be there. R did not find it and I did also not find a help entry for it: > help(extractProbeAnno) No documentation for 'extractProbeAnno' in specified packages and libraries: you could try 'help.search("extractProbeAnno")' However, I could use for example posToProbeAnno and find the corresponding help page?! Here is the session info: > sessionInfo() R version 2.7.2 (2008-08-25) i386-pc-mingw32 locale: LC_COLLATE=Norwegian (Bokm?l)_Norway.1252;LC_CTYPE=Norwegian (Bokm?l)_Norway.1252;LC_MONETARY=Norwegian (Bokm?l)_Norway.1252;LC_NUMERIC=C;LC_TIME=Norwegian (Bokm?l)_Norway.1252 attached base packages: [1] splines tools stats graphics grDevices utils datasets methods base other attached packages: [1] Ringo_1.4.0 SparseM_0.78 RColorBrewer_1.0-2 vsn_3.6.0 affy_1.18.2 [6] preprocessCore_1.2.1 affyio_1.8.1 geneplotter_1.18.0 annotate_1.18.0 xtable_1.5-4 [11] AnnotationDbi_1.2.2 RSQLite_0.7-1 DBI_0.2-4 lattice_0.17-13 genefilter_1.20.1 [16] survival_2.34-1 Biobase_2.0.1 limma_2.14.7 loaded via a namespace (and not attached): [1] grid_2.7.2 KernSmooth_2.22-22 Beyond the problems with getting the autocorrelation I was wondering if there is a good way to judge the quality of Ringo peak detection or the probability of getting wrong hits or loosing some? Thanks for any help, Torsten -----Original Message----- From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor- bounces@stat.math.ethz.ch] On Behalf Of Joern Toedling Sent: 30. juni 2009 13:12 To: Torsten Waldminghaus; bioconductor at stat.math.ethz.ch Subject: Re: [BioC] Missing Autocorrelation in Ringo Hello, to clarify, do you mean that the plot does not show anything or that the plot indicates that there is no correlation? Is there an error message or warning? If so, what does it say? Further questions that could help me to figure out what is going on. What is the result of str(exAc) ls(annoObject) head(annoObject["1.start"]) Note that if your Agilent ChIP-chip files follow their convention to encode the probe position in a colum called "SystematicName" then you can also use the function "extractProbeAnno" on the RGList to obtain a probeAnno object. Last but not least, what is the output of sessionInfo()? Please always specify that when posting a question on the Bioconductor mailing list so that we can figure out if there might be problem with the package versions. Best regards, Joern0 On Mon, 29 Jun 2009 14:17:00 +0200, Torsten Waldminghaus wrote > Dear all, > > I started using the Ringo package to analyze ChIP on Chip data and tried > to make a nice plot of my nice autocorrelation. However, the plot shows > no autocorrelation of neighbouring probes. This is unlikely to be > because of the bad data, because I see really nice peaks when I plot > signals on the chromosomal position and it fits very well with published > data. If anybody has a suggestion what could be wrong or how I could > find out what's wrong I would be happy. > > This is what I do in more detail: > > > RG <- read.maimages(files,"agilent")#read in array data > > I wrote an annotation file which looks like this ("POSITIONS" and > "PROBE_ID" come from the RG file above): > > > annotationFile[1:3,] > > CHROMOSOME PROBE_ID POSITION LENGTH > > 1 1 2 218268 60 > > 2 1 3 2239049 60 > > 3 1 6 3448934 60 > > This I used to make a probeAnno object like this: > > > annoObject<-posToProbeAnno (annotationFile) > > Than I calculate autocorrelation: > > > exAc<-autocor(RG,probeAnno=annoObject, chrom="1",lag.max=1000) > > And plot: > > > plot(exAc) > > Thanks for any help, > > Torsten _______________________________________________ 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
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Hi Torsten, I suggest that you first update your R and Bioconductor installation as you are using very out-dated versions of both (R is currently 2.9.0 and for Ringo please use the current development version (1.9.5), which can be downloaded as a binary from here: http://www.bioconductor.org/packages/devel/bioc/html/Ringo.html ). In the current version of Ringo, you will also find the function extractProbeAnno. And indeed such a low degree of autocorrelation is unexpected. What was the length distribution of fragments after sonication? Typically you would expect some auto-correlation at least up to that length. This factor is also important for setting the sliding-window width for smoothing the signal prior to peak detection. However, your data objects look alright, so I am afraid that I do not immediately see the problem. For judging the quality of the found "peaks", you can resort to visualizations of a.) the highest-ranking peaks b.) the lowest-ranking peaks c.) positive control regions where you would expect peaks d.) negative control- regions where no enrichment is to be expected. Usually the "null distribution" of smoothed probe levels under non- enrichment can only roughly be estimated from the data based on certain simplifying assumptions, so I would not lend too much confidence to p-values and FDRs from such estimates. Regards, Joern On Tue, 30 Jun 2009 14:04:31 +0200, Torsten Waldminghaus wrote > Hi, > > thanks for the answer and sorry for not making it more clear. I get > a plot but it suggests that there is no autocorrelation. This means > the column at point "0" is at 1.0 as usual but at "100", "200",... > there are only dots which vary a bit in their size. Now the results > you were interested in: > > > str(exAc) > Class 'autocor.result' atomic [1:11] 1.00000 -0.00469 -0.00660 > 0.00538 0.00652 ... ..- attr(*, "chromosome")= chr "1" > > > ls(annoObject) > [1] "1.end" "1.index" "1.start" "1.unique" > > > head(annoObject["1.start"]) > [1] 68 154 189 294 365 440 > > I tried the function extractProbeAnno but it does actually not seem > to be there. R did not find it and I did also not find a help entry > for it: > > > help(extractProbeAnno) > No documentation for 'extractProbeAnno' in specified packages and libraries: > you could try 'help.search("extractProbeAnno")' > > However, I could use for example posToProbeAnno and find the > corresponding help page?! > > Here is the session info: > > > sessionInfo() > R version 2.7.2 (2008-08-25) > i386-pc-mingw32 > > locale: > LC_COLLATE=Norwegian (Bokm?l)_Norway.1252;LC_CTYPE=Norwegian (Bokm?l) > _Norway.1252;LC_MONETARY=Norwegian (Bokm?l) > _Norway.1252;LC_NUMERIC=C;LC_TIME=Norwegian (Bokm?l)_Norway.1252 > > attached base packages: > [1] splines tools stats graphics grDevices utils > datasets methods base > > other attached packages: > [1] Ringo_1.4.0 SparseM_0.78 RColorBrewer_1.0-2 > vsn_3.6..0 affy_1.18.2 [6] preprocessCore_1.2.1 > affyio_1.8.1 geneplotter_1.18.0 annotate_1.18.0 > xtable_1.5-4 [11] AnnotationDbi_1.2.2 RSQLite_0.7-1 > DBI_0.2-4 lattice_0.17-13 genefilter_1.20.1 [16] > survival_2.34-1 Biobase_2.0.1 limma_2.14.7 > > loaded via a namespace (and not attached): > [1] grid_2.7.2 KernSmooth_2.22-22 > > Beyond the problems with getting the autocorrelation I was wondering > if there is a good way to judge the quality of Ringo peak detection > or the probability of getting wrong hits or loosing some? > > Thanks for any help, > Torsten
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Hi, Don't mean to intrude, but small correction: > I suggest that you first update your R and Bioconductor installation > as you > are using very out-dated versions of both (R is currently 2.9.0 and > for Ringo The latest version of R is currently 2.9.1 :-) -steve -- Steve Lianoglou Graduate Student: Physiology, Biophysics and Systems Biology Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact
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