exactly, I realize the color maybe used for mapping, I am working on a solution like this step 1. clear the panel grid first by using theme() step 2. add grid line manually, this is very tricky, because the data is transformed to not over integer limits, check out metadata(p@data) you will see some meta data come from biovizBase::transformToGenome() function, also space between chromosome added, case even get complicated when your original data has or doesn't have seqlengths, I will get back to you on this asap this afternoon cheers Tengfei On Wed, Mar 26, 2014 at 10:50 AM, Julian Gehring wrote: > Hi Tengfei, > > Separating by color works nicely, but becomes problematic here because I > want to encode another entity by color. > > Is it possible to add 'vlines' on top of the existing plot? I have > tried it with > > p + autoplot(x, aes(xintercept = start), geom = "vline", coord = > "genome") > > but without success. > > Best wishes > Julian > > > On 26/03/14 15:30, Tengfei Yin wrote: > > first existing 'official' solution to separate group easily is to use > > 'color' parameters in "plotGrandLinear" function, you can assign a > > vector of color (2, or 3 or length of chromosome) and this will be > > cycled and assigned to each group > > > > plotGrandLinear(gr.snp, aes(y = pvalue), color = c("#7fc97f", "#fdc086")) > > > > I forget to document this color parameters in plotGrandLinear, I do have > > them in the example of manual, but autoplot() doesn't support this > > special color assignment yet. > > > > Inline image 1 > > I need to work on a theme() solution if you still want to put line > > between chromosome. > > > > cheers > > > > Tengfei > > > > > > > > On Wed, Mar 26, 2014 at 10:15 AM, Tengfei Yin > > > wrote: > > > > oh wait, sorry, you are talking about plotGranlinear, not layout > > karyogram... I guess I need a coffee in the morning first :) let me > > check to see if there is any quick workaround. > > > > cheers > > > > Tengfei > > > > > > On Wed, Mar 26, 2014 at 10:08 AM, Tengfei Yin > > > > wrote: > > > > Hi Julian, > > > > yes, you could use ylim parameter in layout_karyogram() to > > control this and to layout different group at different height > > layer by layer, because by default the chromosome height limits > > are [0, 10], if you set ylim outside the region like [10, 15], > > it will plot them outside, an example to plot different group at > > different height is shown below, I know it's just a workaround, > > I probably need to provide a simpler way > > > > ######## > > library(ggbio) > > data(hg19IdeogramCyto, package = "biovizBase") > > data(hg19Ideogram, package = "biovizBase") > > library(GenomicRanges) > > ## simul_snp > > chrs <- as.character(levels(seqnames(hg19IdeogramCyto))) > > seqlths <- seqlengths(hg19Ideogram)[chrs] > > set.seed(1) > > nchr <- length(chrs) > > nsnps <- 100 > > gr.snp <- GRanges(rep(chrs,each=nsnps), > > IRanges(start = > > do.call(c, lapply(chrs, > function(chr){ > > N <- seqlths[chr] > > runif(nsnps,1,N) > > })), width = 1), > > SNP=sapply(1:(nchr*nsnps), function(x) > > paste("rs",x,sep='')), > > pvalue = -log10(runif(nchr*nsnps)), > > group = sample(c("Normal", "Tumor"), size = > > nchr*nsnps, > > replace = TRUE) > > ) > > gr.snp > > ##names(seqlths) <- gsub("chr", "", names(seqlths)) > > seqlths > > seqlengths(gr.snp) <- seqlths[names(seqlengths(gr.snp))] > > gr.snp.bac <- gr.snp > > seqinfo(gr.snp) > > gr.snp <- keepSeqlevels(gr.snp, c("chr1", "chr2", "chr3", > "chr4")) > > > > ## above this line is just creating simulated data > > ## suppose you have your snp data store in gr.snp > > ## you have to split the group for now, sorry > > grl.snp <- split(gr.snp, gr.snp$group) > > grl.snp > > > > autoplot(seqinfo(grl.snp)) + layout_karyogram(data = > > grl.snp[[1]], color = "red", ylim = c(0, 10) ) + > > layout_karyogram(data = grl.snp[[2]], color = "blue", ylim = > > c(10, 20) ) > > > > ######### > > > > HTH > > > > Tengfei > > > > > > On Wed, Mar 26, 2014 at 8:49 AM, Julian Gehring > > > wrote: > > > > Hi, > > > > The 'plotGrandLinear' or the respective 'autoplot' function > > of the > > 'ggbio' package make it easy to visualize all the > > chromosomes of a > > genomes together. For example: > > > > autoplot(gr.snp, coord = "genome", geom = "point", aes(y = > > pvalue), > > space.skip = 0.01) ## taken from 'example(plotGrandLinear' > > > > produces a plot for all human chromosomes with vertical > > lines in the > > middle of each chromosome. Can one easily adapt this, in > > the way that > > the vertical lines fall between the chromosomes? This would > > be helpful > > for distinguishing/separating them. > > > > Best wishes > > Julian > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor@r-project.org Bioconductor@r-project.org> > > https://stat.ethz.ch/mailman/listinfo/bioconductor > > Search the archives: > > > http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > > > > > > > -- > > Tengfei Yin, PhD > > Seven Bridges Genomics > > sbgenomics.com > > 625 Mt. Auburn St. Suite #208 > > Cambridge, MA 02138 > > (617) 866-0446 > > > > > > > > > > -- > > Tengfei Yin, PhD > > Seven Bridges Genomics > > sbgenomics.com > > 625 Mt. Auburn St. Suite #208 > > Cambridge, MA 02138 > > (617) 866-0446 > > > > > > > > > > -- > > Tengfei Yin, PhD > > Seven Bridges Genomics > > sbgenomics.com > > 625 Mt. Auburn St. Suite #208 > > Cambridge, MA 02138 > > (617) 866-0446 > -- Tengfei Yin, PhD Seven Bridges Genomics sbgenomics.com 625 Mt. Auburn St. Suite #208 Cambridge, MA 02138 (617) 866-0446 [[alternative HTML version deleted]]