Back again. Is there a quick way to add the sample names in the plot? I was not able to find anything other than creating a new category with the name in it (and the same color all over). Thanks, Michele
On Nov 14, 2012, at 2:45 PM, michele caseposta wrote: > Hi Jim, > sizetree was what I was looking for. > I am going to play with the options a bit. > Thanks a lot, > Michele > > On Nov 14, 2012, at 2:55 AM, Jim Lemon wrote: > >> On 11/14/2012 11:04 AM, michele caseposta wrote: >>> Hi everyone, >>> I have a certain number of samples and I want to visualize the groups those >>> samples belong to. >>> For example, suppose to have three variables, age, sex, and >>> smoker/nonsmoker, and three samples, S1, S2, S3. >>> S1 is 35, male, nonsmoker >>> S2 is 24, female, nonsmoker >>> S3 is 24, female, smoker >>> >>> at the end I have the following data frame: >>> >>> S1 S2 S3 >>> age 35 24 30 >>> sex M F F >>> smk N N S >>> >>> What I would like is to see this represented in a matrix with colors >>> representing the group the specific sample belongs to. In the example, Age >>> would have three levels, sex and smoker/nonsmoker will have two. >>> >>> An example of what I would like to obtain is from the attached image (from >>> The Cancer Genome Browser at UCSC) >>> You can see the class of each sample represented by the color. >>> Clearly here there are useless variables, like sample name, but the example >>> gives an idea of what I would like to get. >>> >>> So far I was able to achieve a pseudo-result with colorbar.plot, but I find >>> it hard to get the labels in the correct position, as it seems like I >>> cannot find a way to automatically put them near each class bar >>> >>> Any suggestions other than colorbar.plot? >>> >> Hi michele, >> Your picture didn't come thought, but it was fairly easy to find. I'm not >> entirely sure about this, but are you looking for an hierarchic breakdown of >> your variables? The illustration on the right side of your example looks >> like this. Sizetrees provide such a breakdown by successive stacked bars, in >> which each bar in the leftmost stack splits into its components, like smoke >> -> sex -> age. Alternatively you can illustrate relationships like these >> with nested bar plots, in which subcategories are nested within the >> superordinate categories. See the sizetree and barNest functions in the >> plotrix package. >> >> Jim >> > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
