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Hi, I have many files containing one column of data. I like to use the scan function to parse the data. Next I like to bind to a large vector. I try this like: count<-1 files <- list.files() # all files in the working directory for(i in files) { tmp <- scan(i) assign(files[count], tmp) count<-count+1 } This part works! Now I like to plot the data in a boxplot.

Hi, I have a question concerning the image function and how to generate custom axis labels: dat<-sample(0:1,1000,replace=T) matrix(dat,ncol=5,nrow=200)->x x[order(x[,1],x[,2],x[,3],x[,4],x[,5]),]->x I would like to have a heatmap kind of thing like this: image(t(x),col=c(0,1),axes=F) axis(1, 1:5, c(colnames(x))) I only do see parts of the axis (only an "A" is

Hi, I'm stuck with parsing data into R for heatmap representation. The data looks like: 1 id1 x1 x2 x3 .... x20 2 id1 x1 x2 x3 .... x20 3 id1 x1 x2 x3 .... x20 4 id1 x1 x2 x3 .... x20 ......... 348 id2 x1 x2 x3 .... x20 349 id2 x1 x2 x3 .... x20 350 id2 x1 x2 x3 .... x20 351 id2 x1 x2 x3 .... x20 ......... The data is sorted for the IDs (id1,id2 .....id40) and I like to

Hi, please excuse the most likely very trivial question, but I'm having no idea where to find related information: I try to recapitulate very simple plotting behavior of Excel within R but have no clue how to get where I want. I have tab delimited data like cell treatment value line a treat1 4 line a treat2 3 line b treat1 8 line b treat2 11 I'd like to have a plot (barplot), that

Hi, I have a very simple question, but I'm obviously not able to solve the problem on my own. I have a data.frame like sample(c("A","B","C"),size=20,replace = T)->type rnorm(20)->value data.frame(ty=type,val=value)->test There must be some built in functions, that will do some descriptive statistics with tabular output, in the end I like to have

Hi, I have a question concerning the analysis of some affymetrix chips. I downloaded some of the data from GEO GSE11324 (see below). In doing so I'm stuck after I identified the probesets with significant changes. I have problems in assigning probeset specific gene names as well as getting the genomic coordinates. Furthermore I have no clue how to deal with the fact, that most genes have

Hi, I'm trying to merge a couple of matrices together. The matrices are created from a couple of input files that have very similar (but not in all cases) values in first and second column. 1st and 2nd column are used to generate rownames, the actually interesting value is in column 3. I'd like to merge the different files by the rownames generated from 1st and 2nd column. Files look like

Hi, I have a question about how to sort a matrix for multiple columns. dat<-sample(0:1,1000,replace=T) matrix(dat,ncol=5,nrow=200)->x I want to order like the following: x[order(x[,1],x[,2],x[,3],x[,4],x[,5]),]->x My problem: the number of columns of the matrix to be sorted is variable, in any way I would like to sort for all columns from 1:ncol(x). How to achieve this? Best

Hi, I have to plot a heat map and next to it a lineplot. Unfortunately the scale is not the same between the two plots (as the heatmap data is binned). My problem is, that despite the fact the plotted areas (marked by the heatmap and box of the the default line plot) are essentially very similar, the coordinate system is slightly shifted. Below code does not produce as bad results as I have on

Hello, I'm having a question related to the system command within R: I try to evoke a perl script from within R with something like system(paste('perl myscript.pl', some parameters ....,sep=" ") This works just fine as long as I do not use any additionally installed Perl module, as this leads to a "Can't locate Statistics/Descriptive.pm in @INC ....." This

Hi, I have a gene expression experiment with 20 samples and 25000 genes each. I'd like to perform clustering on these. It turned out to become much faster when I transform the underlying matrix with t(matrix). Unfortunately then I'm not anymore able to use cutree to access individual clusters. In general I do something like this: hc <- hclust(dist(USArrests), "ave")