Missing Autocorrelation in Ringo
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@torsten-waldminghaus-3502
Last seen 8.1 years ago
Hi Joern, I did do some updating. This is how it looks like now: > sessionInfo() R version 2.9.1 (2009-06-26) 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] grid stats graphics grDevices datasets utils methods base other attached packages: [1] Ringo_1.9.5 Matrix_0.999375-29 lattice_0.17-25 limma_2.18.2 RColorBrewer_1.0-2 [6] Biobase_2.4.1 loaded via a namespace (and not attached): [1] annotate_1.22.0 AnnotationDbi_1.6.1 DBI_0.2-4 genefilter_1.24.2 RSQLite_0.7-1 [6] splines_2.9.1 survival_2.35-4 xtable_1.5-5 I coul now also find and use the extractProbeAnno function but get this: > test<-extractProbeAnno(RG) Creating probeAnno mapping for chromosome Error in split.default(probeindex, as.factor(hits[[chrNameColumn]])) : Group length is 0 but data length > 0 In addition: Warning message: In extractProbeAnno(RG) : Some reporters had no or an unrecognized genome position in RG$genes$SystematicName. You said that the function works with an RGlist object if it" encodes the probe position in a colum called "SystematicName"". This is the case but it looks like this: > RG$genes$SystematicName[100] [1] "CGH_U00096_943375_943434_a" Is this what you ment? I also tried the autocorraltion again as before but did get the same strange result. Could it be that it is a problem that the data in the RG file are not ordered? I had problems with that when I used some other peak detection because the program looked just at the next entry without considering the probe position. My DNA fragments where 1000bp and smaller with a peak at 500bp. About the judging of quality of found peaks, could you explain what " resort to visualizations" means and how I would do this practically. Many thanks, Torsten -----Original Message----- From: Joern Toedling [mailto:Joern.Toedling@curie.fr] Sent: 30. juni 2009 16:40 To: Torsten Waldminghaus; bioconductor at stat.math.ethz.ch Subject: Re: [BioC] Missing Autocorrelation in Ringo 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
probe Ringo probe Ringo • 767 views
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@joern-toedling-3465
Last seen 8.1 years ago
Hello, please find the answers below your questions. > I coul now also find and use the extractProbeAnno function but get this: > > > test<-extractProbeAnno(RG) > Creating probeAnno mapping for chromosome Error in > split.default(probeindex, as.factor(hits[[chrNameColumn]])) : > Group length is 0 but data length > 0 In addition: Warning message: > In extractProbeAnno(RG) : Some reporters had no or an unrecognized > genome position in RG$genes$SystematicName. > > You said that the function works with an RGlist object if it" > encodes the probe position in a colum called "SystematicName"". This > is the case but it looks like this: > > > RG$genes$SystematicName[100] > [1] "CGH_U00096_943375_943434_a" > > Is this what you ment? No, not really. With Agilent ChIP-chip that I have seen previously their output contained a column SystematicName that looked like this chr17:033719613-033719665 and this is obviously what the parser what is written for. So I am afraid you have to either rewrite extractProbeAnno for your data or generate the "pos" data.frame by hand and then call function posToProbeAnno. > > I also tried the autocorraltion again as before but did get the same > strange result. Could it be that it is a problem that the data in > the RG file are not ordered? I had problems with that when I used > some other peak detection because the program looked just at the > next entry without considering the probe position. My DNA fragments > where 1000bp and smaller with a peak at 500bp. Well, in that case you obviously should have some degree of auto- correlation at least up to 500bp. I cannot tell what went wrong as I have not come across this problem before. The fact that the probes are not sorted should not matter, as the probe positions are taken from the probeAnno object and not from the row ordering of the RGList. If you want, I could have a more thorough look into this, if you send me (off list!) the RGList and the "pos" data.frame for the probeAnno. > About the judging of quality of found peaks, could you explain what > " resort to visualizations" means and how I would do this practically. The vignette of the package contains examples of how to visualize a.) your data in any genomic region that you specify b.) the identified peaks Please follow these examples and contact me if there are further questions. Best regards, Joern --- Joern Toedling Institut Curie -- U900 26 rue d'Ulm, 75005 Paris, FRANCE Tel. +33 (0)156246926
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