Plotting data from a bedGraph file
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@michael-hoffman-3494
Last seen 10.3 years ago
I have a couple of bedGraph files (similar to wiggle tracks in BED style) with scores associated with almost every region of the human genome. I have been comparing these with the UCSC genome browser but I would prefer to look at all chromosomes simultaneously. I considered compare them visually with something like cPlot() in geneplotter. But at first glance, by reading through some examples this appears to be more appropriate for microarray data rather than arbitrarily defined genomic regions. Eventually I just read in the data like this: gm12878 <- read.table(gzfile("gm12878.bedGraph.gz"), col.names = c("chrom", "chromStart", "chromEnd", "dataValue"), skip=1) Then I can use xyplot(dataValue ~ chromStart | chrom, gm12878) for a crude approximation of what I want. But I was wondering if there was something out there a little more polished, whether in Bioconductor (I was hoping) or elsewhere. Thanks! Michael Hoffman
Microarray Microarray • 2.7k views
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@michael-lawrence-2759
Last seen 10.3 years ago
On Fri, Jun 5, 2009 at 3:18 PM, Michael Hoffman <9qobl2n02@sneakemail.com>wrote: > I have a couple of bedGraph files (similar to wiggle tracks in BED style) > with scores associated with almost every region of the human genome. I have > been comparing these with the UCSC genome browser but I would prefer to look > at all chromosomes simultaneously. > Maybe the ideogram package would help? > > I considered compare them visually with something like cPlot() in > geneplotter. But at first glance, by reading through some examples this > appears to be more appropriate for microarray data rather than arbitrarily > defined genomic regions. Eventually I just read in the data like this: > > gm12878 <- read.table(gzfile("gm12878.bedGraph.gz"), col.names = c("chrom", > "chromStart", "chromEnd", "dataValue"), skip=1) > > Then I can use xyplot(dataValue ~ chromStart | chrom, gm12878) for a crude > approximation of what I want. But I was wondering if there was something out > there a little more polished, whether in Bioconductor (I was hoping) or > elsewhere. > > Thanks! > > Michael Hoffman > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > [[alternative HTML version deleted]]
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@wolfgang-huber-3550
Last seen 3 months ago
EMBL European Molecular Biology Laborat…
Hi Michael have you considered the GenomeGraphs (and possibly, rtracklayer) packages? Best wishes Wolfgang ------------------------------------------------ Wolfgang Huber, EMBL, http://www.ebi.ac.uk/huber Hoffman ha scritto: > I have a couple of bedGraph files (similar to wiggle tracks in BED > style) with scores associated with almost every region of the human > genome. I have been comparing these with the UCSC genome browser but I > would prefer to look at all chromosomes simultaneously. > > I considered compare them visually with something like cPlot() in > geneplotter. But at first glance, by reading through some examples this > appears to be more appropriate for microarray data rather than > arbitrarily defined genomic regions. Eventually I just read in the data > like this: > > gm12878 <- read.table(gzfile("gm12878.bedGraph.gz"), col.names = > c("chrom", "chromStart", "chromEnd", "dataValue"), skip=1) > > Then I can use xyplot(dataValue ~ chromStart | chrom, gm12878) for a > crude approximation of what I want. But I was wondering if there was > something out there a little more polished, whether in Bioconductor (I > was hoping) or elsewhere. > > Thanks! > > Michael Hoffman > > _______________________________________________ > 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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Thanks to Wolfgang and Michael for your helpful replies. GenomeGraphs is a lot closer to what I'm looking for, but I have almost 2 million regions and it seems a bit slow in dealing with large numbers of data rows. I think I will stick with using lattice and xyplot() which is fast enough. This is still useful information for the future though. Thanks. Michael Wolfgang Huber wrote: > Hi Michael > > have you considered the GenomeGraphs (and possibly, rtracklayer) packages? > > Best wishes > Wolfgang > > ------------------------------------------------ > Wolfgang Huber, EMBL, http://www.ebi.ac.uk/huber > > > Hoffman ha scritto: >> I have a couple of bedGraph files (similar to wiggle tracks in BED >> style) with scores associated with almost every region of the human >> genome. I have been comparing these with the UCSC genome browser but I >> would prefer to look at all chromosomes simultaneously. >> >> I considered compare them visually with something like cPlot() in >> geneplotter. But at first glance, by reading through some examples >> this appears to be more appropriate for microarray data rather than >> arbitrarily defined genomic regions. Eventually I just read in the >> data like this: >> >> gm12878 <- read.table(gzfile("gm12878.bedGraph.gz"), col.names = >> c("chrom", "chromStart", "chromEnd", "dataValue"), skip=1) >> >> Then I can use xyplot(dataValue ~ chromStart | chrom, gm12878) for a >> crude approximation of what I want. But I was wondering if there was >> something out there a little more polished, whether in Bioconductor (I >> was hoping) or elsewhere. >> >> Thanks! >> >> Michael Hoffman >> >> _______________________________________________ >> 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 > > _______________________________________________ > 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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