similar to: qplot: plotting precipitation data

DeaR list, I'm trying to represent some information via 3D plots. My data and session info are at the end of this message. So far, I have tried scatterplot3d (scatterplot3d), persp3d (rgl), persp (graphics) and scatter3d (Rmcdr) but any of them gave me what I'd like to have as final result (please see [1] for a similar 3D plot changing PF by ypred, pdn by h4 and pup by h11). In general

I have the following xyplot figure: http://img577.imageshack.us/img577/686/filesizeresults12000000.png The data are organized in a matrix file as follows: Type Elements Chromosome Time bedGz 12000000 chr1 14.240 bedGz 12000000 chr2 7.949 bedGz 12000000 chr3 5.103 bedGz 12000000 chr4 5.290 bedGz 12000000 chr5 5.161 ... The x-axis labels in the Chromosome column are ordered

Greetings, I am new to R, but trying to put in the time to learn. I have read the R manual and several other introductory texts; however, there is nothing like actually putting it into practice. So here is my problem, and its more of a learning exercise for myself than anything else, but I'm stuck and getting extremely frustrated that I can't figure it out. I'm trying to make a

Hello, I have an input file: http://r.789695.n4.nabble.com/file/n3700031/testOut.txt testOut.txt where col 1 is chromosome, column2 is start of region, column 3 is end of region, column 4 and 5 is base position, column 6 is total reads, column 7 is methylation data, and column 8 is the strand. I would like a summary output file such as:

Hi, I was wondering I'm going about this in the correct way. I need to test if there are coding sequences or exons in hg19 which match a string of 100bp "D" i.e. [A,G or T]. However I'm getting a strange result. I get a hit on chr7, using the 100bp search however when I search with 60bp sequence of "D" I don't get any hits. library("BSgenome")

Thanks for the reprex. Wouldn't have bothered without it. The following is I believe **almost** what you want. It seems a bit clumsy to me, so others may provide you something neater. But anyway... ## Convert POSIXct vector to dates ## There are 22 different days, not 21 date <- as.Date(prec_idx) ## Sum results by date at each i,j of the last 2 array dimensions z <-

Using the small reproducible example below, I'm wondering how best to complete the following task: In the small reproducible example below, the 3D array prec has indexes that correspond to time, x, y (i.e., prec[time, x, y]). In this case, the time index is hours since some predefined start time. I'd like to add up all the time indexes in 'prec' based on whether or not the