similar to: Data.matrix fail to convert data.frame into matrix

Hi, How can I partitioned an example vector like this > print(myvector) [1] 30.9 60.1 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 into the following pairwise partition: PAIR1 part1 = 30.9 part2 = 60.1 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 PAIR2 part1 = 30.9 60.1 part2 = 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 .... PAIR9 part1 = 30.9

Hello all! I am currently trying to sort a data frame in a particular way, but I am having some difficulties with this. Specifically I want to sort the below dataset in such a way that there is only one line per ProteinID and if there are multiple GeneID or GeneName entries for a single proteinID, that they be concatenated with a comma separating them. The way I have done it earlier worked fine

I'm trying to find a clever way to re-map data from a database query into a data.frame. Querying a database often returns a table (data.frame) like this: GeneID MethodID Value 6 1 123 6 2 456 6 3 987 7 1 234 7 3 432 8 2 190 8 3 34 8 1 864 Note that GeneID=7 doesn't have a value for MethodID=2. Note that GeneID=8 doesn't have the

Hi, I'm a bit puzzled by the gamlss fitting of exponential and lognormal data. Gamlss seems to think that exponentially distributed data fits better with a lognormal distribution, and vice versa. For example, X <- rexp(1000) Gexp <- gamlss(X~1,family=EXP) # X~1 is X tilde 1 GAMLSS-RS iteration 1: Global Deviance = 2037.825 GAMLSS-RS iteration 2: Global Deviance = 2037.825 Glno

Is there any function/way to merge/unite the following data GENEID col1 col2 col3 col4 G234064 1 0 0 0 G234064 1 0 0 0 G234064 1 0 0 0 G234064 0 1

Hi, i have two files (file1.txt and file2.txt) which i would like to merge, based on certain criteria, i.e. it combines data based on matching geneID and exons. i have used the merge option, but it does not give me the desired outcome. merged.txt shows the result i would like. *File1. txt* ** AffyProbe ProbeType Flag GeneSymbol GeneID Exons Chrom Strand Affytart AffyEnd 1

Dear all, I want to use string split to parse column names, however, I am having some errors that I don't understand. I see a problem when I try to rbind the output from strsplit. please let me know if I'm missing something obvious, thanks, alison here are my commands: >strsplit<-strsplit(as.character(Rumino_Reps_agreeWalign$geneid),"\\.") >

Dear All: I have a question on using coxph for multiple genes: I have written code to loop through all 22283 genes in the Hgu-133A and apply coxph on survival data. However, I don't know how to work with the result for each gene: survtest<-coxph(Surv(pcc.primary.stg.3.cox[,'fup_interval'],pcc.primary.stg.

Hello, I'm trying to run constrOptim. It returns to me an error about the fact that constraints arguments (ui and ci) are non compatibles: > optout= constrOptim(startparams, f=ImpulseSS, grad=grImpulse, ui=UI, ci=CI, data=gexp[k,], t=t) Error in ui %*% theta : non-conformable arguments I would like to point out that I can calculate that product in the command line: > UI %*%

Hi all, I've tried to plot a vector which has two peaks in the density. This link shows the figure. http://docs.google.com/View?docid=dcvdrfrh_1dk9r2rc7 The red line is normal curve and green line is gamma curve. Notice that red line can correctly fit the histogram that has two peaks (i.e. red curve also has two peaks). But the gamma curve there only has one curve. Is there a way I can

Dear all, I have a simple plot using "gridBase" like this. The problem occurs whenever I execute this code there is always a blank page created before the actual plot. How can we disable that blank page? I am using: R version 2.7.2 (2008-08-25) and gridBase version: 0.4-3 __ BEGIN__ library(grid) library(gridBase) opar <- par(no.readonly=TRUE) par(opar) grid.newpage()

Dear List, I am trying to modify the xlab and ylab for a current figure that was plotted by a package, I searched through the low level plotting command and they do not seem to contain how to do this (the only way is to use xlab, ylab as arguments in "plot" command, which I can not do since the plot is plotted using some other package, not by my own script). Is there any command for

Hi, I have two figures where I stacked together as one PNG. Top -> scatter plot Bottom -> density plot. However these two figures are squeezed together as rectangle figures each. (i.e. the y axes are compressed) Is there a way I can resize the figure? So that it can show proportional and complete plots? The code I have is the following: (I can also provide the figure if needed).

I am trying to use a new (to me) package (samr) and even when I try to run a very simple example, I get this "cannot open the connection" error. The reason I am writing to r-help rather than to the authors of samr is I think this may be a more general R problem rather than a samr-specific problem. Perhaps something with my installation and write access to some particular place ? I am

Dear All, I?m using lme to analyze a time series gene expression data. I don?t have all animals in all times, the number of animals in each time is different and I have lots of NA values. An example file can be downloaded at lbmp.fcav.unesp.br/leonardo and the code used is the following: teste<-read.table(file='example.csv',sep=',',header=T) B<-1366 library(nlme)

Hi, i have two files (file1.txt and file2.txt) which i would like to merge, based on certain criteria, i.e. it combines data based on matching geneID and exons. i have used the merge option, but it does not give me the desired outcome. merged.txt shows the result i would like. *File1. txt* ** AffyProbe ProbeType Flag GeneSymbol GeneID Exons Chrom Strand Affytart AffyEnd 1

Hi, I was working on a classification problem using the pamr package. I used the pamr.adaptthresh() function to find the optimal accuracy of the classifier. I must not be doing it right, since it doesn't return the threshold values for optimum classification. For example,if I run it on a dataset, I get the following result using pamr.adaptthresh(): predicted true

Hi, I was working on a classification problem using the pamr package. I used the pamr.adaptthresh() function to find the optimal accuracy of the classifier. I must not be doing it right, since it doesn't return the threshold values for optimum classification. For example,if I run it on a dataset, I get the following result using pamr.adaptthresh(): predicted true (1)

Hi, Sorry about the earlier formatting errors... I was working on a classification problem using the pamr package. I used the pamr.adaptthresh() function to find the optimal accuracy of the classifier. I must not be doing it right, since it doesn't return the threshold values for optimum classification. For example,if I run it on a dataset, I get the following result using

Hi BioC user, I have a problem extracting the gene set I would like to work with. Here is I work with my data: normData <- read.delim("normalizedData.txt",sep ="\t") ######### two class unpaired comparison # y must take values 1,2 classes <- c(-1,-2,1,2) #prepere the data for the samr analysis data.x <-as.matrix(normData[,8:11]) d=list(x=data.x,y=classes,