Hi, A quick question re: data visualisation. I have three tiling arrays, with input and chIP channels. I've run through the commands as outlined in the vignette, substituting bits and pieces to suit my own data, however, I'm having one problem. When I visualise a plot of the smoothed (i.e. preprocessed data, any method), I get a plot output with two data sets - 1)input and 2) chip. I was under the assumption that I should only be seeing the chIP dataset, with the input having been taken into account during preprocessing and not displayed on the graph. Assuming that this 'input' data is mainly background (as it is the sample prior to antibody-aided pulldown), how do I adjust the output visuals so that I can view only the relevant data (chIP), while not just simply 'ignoring' the input data (i.e. I'm assuming it's needed as a 'reference' for the chIP data points). Thanks for any help in advance. -- output of sessionInfo(): R version 2.15.1 (2012-06-22) Platform: i386-apple-darwin9.8.0/i386 (32-bit) locale: [1] en_IE.UTF-8/en_IE.UTF-8/en_IE.UTF-8/C/en_IE.UTF-8/en_IE.UTF-8 attached base packages: [1] tools stats4 splines grid stats graphics grDevices [8] utils datasets methods base other attached packages: [1] xtable_1.7-0 survival_2.36-14 genefilter_1.38.0 [4] annotate_1.34.1 RSQLite_0.11.1 DBI_0.2-5 [7] KernSmooth_2.23-8 IRanges_1.14.4 AnnotationDbi_1.18.3 [10] mclust_4.0 Ringo_1.20.0 limma_3.12.3 [13] RColorBrewer_1.0-5 Matrix_1.0-9 lattice_0.20-10 [16] Biobase_2.16.0 BiocGenerics_0.2.0 loaded via a namespace (and not attached): [1] affy_1.34.0 affyio_1.24.0 BiocInstaller_1.4.7 [4] preprocessCore_1.18.0 vsn_3.24.0 XML_3.9-4 [7] zlibbioc_1.2.0 -- Sent via the guest posting facility at bioconductor.org.

Hello, assuming that you are talking about the Ringo package, I am not sure which parts of the vignette you modified for your own data, but apparently you have been missing a step. In general, the data of ChIP and Input channel are read in, stored as an object of class RGList and then the function "preprocess" obtains some form of probe-wise fold-changes ChIP/input. This step is what you call "taking the input into account" and from that point on, in the vignette ChIP and Input are not considered separately any longer. This step results in an object of class ExpressionSet holding informative values for all probes. Of course, you can obtain such an ExpressionSet in other ways. In the vignette, this is followed up by a smoothing step of the fold-changes. So my first guess would be that you omitted the call of "preprocess" and directly went on to the smoothing. And then of course, you still have ChIP and Input intensities separately. HTH, Joern On 10/16/2012 01:47 PM, John H [guest] wrote: > Hi, > > A quick question re: data visualisation. > > I have three tiling arrays, with input and chIP channels. I've run through the commands as outlined in the vignette, substituting bits and pieces to suit my own data, however, I'm having one problem. When I visualise a plot of the smoothed (i.e. preprocessed data, any method), I get a plot output with two data sets - 1)input and 2) chip. > > I was under the assumption that I should only be seeing the chIP dataset, with the input having been taken into account during preprocessing and not displayed on the graph. Assuming that this 'input' data is mainly background (as it is the sample prior to antibody-aided pulldown), how do I adjust the output visuals so that I can view only the relevant data (chIP), while not just simply 'ignoring' the input data (i.e. I'm assuming it's needed as a 'reference' for the chIP data points). > > Thanks for any help in advance. > > > > -- output of sessionInfo(): > > R version 2.15.1 (2012-06-22) > Platform: i386-apple-darwin9.8.0/i386 (32-bit) > > locale: > [1] en_IE.UTF-8/en_IE.UTF-8/en_IE.UTF-8/C/en_IE.UTF-8/en_IE.UTF-8 > > attached base packages: > [1] tools stats4 splines grid stats graphics grDevices > [8] utils datasets methods base > > other attached packages: > [1] xtable_1.7-0 survival_2.36-14 genefilter_1.38.0 > [4] annotate_1.34.1 RSQLite_0.11.1 DBI_0.2-5 > [7] KernSmooth_2.23-8 IRanges_1.14.4 AnnotationDbi_1.18.3 > [10] mclust_4.0 Ringo_1.20.0 limma_3.12.3 > [13] RColorBrewer_1.0-5 Matrix_1.0-9 lattice_0.20-10 > [16] Biobase_2.16.0 BiocGenerics_0.2.0 > > loaded via a namespace (and not attached): > [1] affy_1.34.0 affyio_1.24.0 BiocInstaller_1.4.7 > [4] preprocessCore_1.18.0 vsn_3.24.0 XML_3.9-4 > [7] zlibbioc_1.2.0 > > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- Joern Toedling, PhD Core Facility Bioinformatics Institute of Molecular Biology gGmbH (IMB) http://www.imb-mainz.de Tel.: +49 6131 39 21528