similar to: help required for GO Annotation problem

I am running R 2.0.0, GOstats 1.1.1 and GO 1.7.0, and when I use the function GOHyperG, I have the following error: w1<-as.list(hgu95av2LOCUSID) w2<-unique(unlist(w1)) set.seed(123) myLL<-sample(w2,100) xx <- GOHyperG(myLL) Error in mget(x, env = GOTERM, ifnotfound = NA) : recursive default argument reference In fact first I tried this function with my locusId ' list (with

Running R2.4.0 on Apple Mac OS X 10.4.8, in Emacs ESS mode, and also R.app. In an attempt to learn a bit more about a particular method (geneNames in package affy) I invoked getMethods("geneNames") which produced geneNames methods, but not the one in affy (output below). I had to know the signature (AffyBatch) in order to find the method > getMethod("geneNames",

hi, all: Just wonder if there is any suggestions in how to get around this cbind error. I created two character lists with identical length. First tried combine the lists together with cbind, then convert the lists to matrix, and tried again. Both faied. Any fix to merge the two lists/matrices? ll<- multiget(ftID, hgu95av2LOCUSID) > class(ll) [1] "list" > sym <-

Dear R-Helpers, I have a data.frame (df) and the head of data.frame looks like ProbeUID ControlType ProbeName GeneName SystematicName 1665 1577 0 pSysX_50_22_1 pSysX_50 pSysX_50 5422 5147 0 pSysX_49_8_1 pSysX_49 pSysX_49 4042 3843 0 pSysX_51_18_1 pSysX_51 pSysX_51 3646 3466 0 sll1514_0_2 sll1514 sll1514

Hi, maybe someone can help me with this: I have a matrix of genes and values: GeneName Value Abc1 10 Abc2 11 Bbc1 -5 Bbc31 2 Ccd 5 Ccd -2 Ccd 7 Dda 5 Dda 10 ..... ..... Zzz3 -1 I would like to

Hi R Developers, Greg is helping me with debugging R on Solaris 10 x64. Please let us know if you have any thoughts or tips that can help us debug this. Thanks, David ************ Using default transfer plist in vector_io: permuting About to write *** caught segfault *** address e8554000, cause 'memory not mapped' Traceback: 1: .External("do_hdf5save", call,

Martin Maechler has suggested that I post this comment to r-devel. It was originally posted to bioconductor. --------------------------------- I'd like to raise the issue of a capitalization convention for naming objects in R. Almost everything in R used to be lowercase but recently there is increasing use of mixed upper/lower case to define names. There is potential for using the

Dear all, I am running R 2.4.1. > library(siggenes); > library(multtest); > cl<-rep(c(0,1),c(3,3)); > sub<-exprs(AffyExpData[,c(1:3,7:9)]); > gn<-geneNames(AffyRAwData); > sam.out<-sam(sub,cl,rand=123,gene.names=gn); We're doing 20 complete permutations > sam.out SAM Analysis for the Two-Class Unpaired Case Assuming Unequal Variances Delta p0

Hi Martin, In using the Cluster Package, I have results for PAM and DIANA clustering algorithms (below "part" and "hier" objects): part <- pam(trout, bestk) # PAM results hier <- diana(trout) # DIANA results GeneNames <- show(RG$genes) # Gene Names are in this object But

I am using heatmap with the arguments below. The title size stays the same no matter what I set cex.main to. Is this expected? Can I adjust the title size in heatmap? Also, the position of the main title is at the very upper edge of the output and if I use a "\n" to stack the title the upper line is out of bounds and doesn't show up. I am outputting to pdf. Any help? Thanks,

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

Hello, I am trying to call R from Perl running on Windows 2000. I have looked through the previous posts regarding running R from Perl and all have referred to the RSPerl package at Omegahat. Unfortunately the documentation for this package specifically states that it only works in Unix at the moment. Does anyone else have any suggestions about the best way to do this in the Windows

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,

Dear list, I have gene expression measurements obtained by PCR on 11 genes, tabulated as a data matrix. I'm attempting to use GSA package to distinguish any significant changes in these genes as a pathway. My response variable is binary, 0=no disease, 1=disease. I have read the PCR data into R as follows: data <-

I can't understand that people still send things like this to R-core... ------- start of forwarded message ------- From: Tineke Casneuf <ticas at psb.ugent.be> Sender: r-core-bounces at stat.math.ethz.ch To: R-core at r-project.org Subject: help(Memory) Date: Wed, 04 Feb 2004 13:39:32 +0100 Dear, I am trying to find a appropriate package to analyse gene expression data from DNA

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

Hi all, My name is Amy, I am a masters student in Bioinformatics at North Carolina State University. I am working on a project and I am trying to use the lumi R package for microarray data analysis. I have shown the sample code here and have questions about modifying the sample code for my own data. lumi package in R, example.lumi, the sample data has 8000 features and 4 samples I have

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

Hello Everybody, I am trying to perform SAM with the samr package. I am using the following code: sink ("R005") library(siggenes) library(samr) library(nnet) A <- as.matrix(read.table("D:\samrgenes1000.txt")) B <- as.matrix(read.table("D:\genenames1000.txt")) y1 <- c(rep(1,20),rep(2,6)) #there are 20 chips of one kind and 6 of the other kind. datasam =

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)