Ringo for Nimblegen ChIP-chip data in GEO
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Yong Li ▴ 190
@yong-li-3321
Last seen 10.2 years ago
Dear all, I wanted to re-analyze a ChIP-chip dataset in GEO. Because it was from Nimblegen I thought Ringo is a good option. Although the raw data in GEO are not in the form as mentioned in the Ringo documentation, I have managed to read in the data with read.maimages and made a RGlist, then did some analysis with Ringo. However I still have a few questions. 1) I don't find any information about spot types so I didn't make any use of spot types. Is this a problem? 2) When I ran > image(rg, 1, channel="green", mycols=c("black","green4","springgreen")) # rg is my RGlist I got error: all(c(dim1, dim2) %in% names(x$genes)) is not TRUE Could anyone explain a little more of this error? 3) The dataset consists of data for three antibodies. I am just interested in data for one antibody, which has two biological replicates. I guess it's better to include only the two samples I am interested in normalization (the step preprocess). Any comments? 4) In the computeRunningMedians step, because I have two replicates and want to combine them, I should use combineReplicates=TRUE. Am I correct? Thanks in advance! Yong > sessionInfo() R version 2.11.1 (2010-05-31) i386-pc-mingw32 locale: [1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252 [3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C [5] LC_TIME=German_Germany.1252 attached base packages: [1] grid stats graphics grDevices utils datasets methods [8] base other attached packages: [1] biomaRt_2.4.0 Ringo_1.12.0 Matrix_0.999375-39 lattice_0.18-8 [5] limma_3.4.4 RColorBrewer_1.0-2 Biobase_2.8.0 rtracklayer_1.8.1 [9] RCurl_1.4-2 bitops_1.0-4.1 loaded via a namespace (and not attached): [1] annotate_1.26.1 AnnotationDbi_1.10.2 Biostrings_2.16.9 [4] BSgenome_1.16.5 DBI_0.2-5 genefilter_1.30.0 [7] GenomicRanges_1.0.9 IRanges_1.6.9 KernSmooth_2.23-3 [10] RSQLite_0.9-1 splines_2.11.1 survival_2.35-8 [13] tools_2.11.1 XML_3.1-0 xtable_1.5-6
Normalization Ringo Normalization Ringo • 1.2k views
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@wolfgang-huber-3550
Last seen 3 months ago
EMBL European Molecular Biology Laborat…
Dear Yong, the image.RGList function expects 'rg$genes', the 'genes' slot of the object 'rg', to be a data frame that contains columns with the x- and y-coordinates of each spot. This information is necessary in order to plot the image. By default, it expects these columns to be named 'X' and 'Y', and you can change that with the 'dim1' and 'dim2' arguments of the function. Try the following: ? image.RGList head(rg$genes) More below, inline. Best wishes Wolfgang Il Oct/10/10 11:08 PM, Yong Li ha scritto: > Dear all, > > I wanted to re-analyze a ChIP-chip dataset in GEO. Because it was from > Nimblegen I thought Ringo is a good option. Although the raw data in GEO > are not in the form as mentioned in the Ringo documentation, I have > managed to read in the data with read.maimages and made a RGlist, then > did some analysis with Ringo. However I still have a few questions. > > 1) I don't find any information about spot types so I didn't make any > use of spot types. Is this a problem? > > 2) When I ran > > image(rg, 1, channel="green", > mycols=c("black","green4","springgreen")) # rg is my RGlist > > I got error: > all(c(dim1, dim2) %in% names(x$genes)) is not TRUE > > Could anyone explain a little more of this error? > > 3) The dataset consists of data for three antibodies. I am just > interested in data for one antibody, which has two biological > replicates. I guess it's better to include only the two samples I am > interested in normalization (the step preprocess). Any comments? Yes. > 4) In the computeRunningMedians step, because I have two replicates and > want to combine them, I should use combineReplicates=TRUE. Am I correct? Yes. However, I would also recommend first to do that step separately per replicate, and to visualise & compare the results, to verify the data quality, before proceeding with averaging. > Thanks in advance! > > Yong > > > sessionInfo() > R version 2.11.1 (2010-05-31) > i386-pc-mingw32 > > locale: > [1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252 > [3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C > [5] LC_TIME=German_Germany.1252 > > attached base packages: > [1] grid stats graphics grDevices utils datasets methods > [8] base > > other attached packages: > [1] biomaRt_2.4.0 Ringo_1.12.0 Matrix_0.999375-39 lattice_0.18-8 > [5] limma_3.4.4 RColorBrewer_1.0-2 Biobase_2.8.0 rtracklayer_1.8.1 > [9] RCurl_1.4-2 bitops_1.0-4.1 > > loaded via a namespace (and not attached): > [1] annotate_1.26.1 AnnotationDbi_1.10.2 Biostrings_2.16.9 > [4] BSgenome_1.16.5 DBI_0.2-5 genefilter_1.30.0 > [7] GenomicRanges_1.0.9 IRanges_1.6.9 KernSmooth_2.23-3 > [10] RSQLite_0.9-1 splines_2.11.1 survival_2.35-8 > [13] tools_2.11.1 XML_3.1-0 xtable_1.5-6 > > _______________________________________________ > 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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