search for: genenames

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

...1.3153 32.689 2.8751e-07 3.5912e-04 624 Unknown -3.6256 6.8986 -31.777 3.3333e-07 3.5912e-04 B 1665 9.8342 5422 8.1650 4042 8.0758 3646 7.9408 2946 7.7822 624 7.6622 I want to "collapse" this data frame into a new data.frame so that the df$GeneName contains no duplicate GeneNames (for eg: sll1514) AND the df$logFC contains the average of df$logFC corresponding to these GeneNames (which had duplicate genenames). I am aware of an inefficient strategy using loops, but I believe that there should be a way using Apply functions or may be plyr? I am not able to think of one at...

...11 Bbc1 -5 Bbc31 2 Ccd 5 Ccd -2 Ccd 7 Dda 5 Dda 10 ..... ..... Zzz3 -1 I would like to create a new matrix where the GeneNames which are duplicated and do not have the absolut maximum value between these duplicated genes, are deleted; i.e. GeneName Value Abc1 10 Abc2 11 Bbc1 -5 Bbc31 2 Ccd 7 Dda 10 ........

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", "AffyBatch") Isn't getMethods() suppo...

Dear Sir/Madam, I found your email address and your correspondence with R-users. I hope you could help me with this question about the function "ur.ers" in the package of "urca". It is an improved unit root test (Elliott et al. 1996 Econometrica). Do you know how to extract the value of the test statistic from the output? The only thing I can get is the print-out of all

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

...tware development for computational biology and bioinformatics" by Robert C Gentleman et al., 2004. Generating Heatmaps till Fig2 is working so I think esetSel is not the problem.. However, for generating the Figure 3, for GO annotations the following command is not working: > ll <- mget(geneNames(esetSel),hgu95av2LOCUSID)    #it is displaying error messages  Error in mget(geneNames(esetSel), hgu95av2LOCUSID) : object 'hgu95av2LOCUSID' not foundand also geneNames not found try featureNames instead Hence I cant proceed to the next set of commands provided in the paper which are as fol...

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

...r plist in vector_io: permuting About to write *** caught segfault *** address e8554000, cause 'memory not mapped' Traceback: 1: .External("do_hdf5save", call, sys.frame(sys.parent()), fileout, ..., PACKAGE = "hdf5") 2: hdf5save(hdf5_Fstat, "Fstat", "geneNames", "genotype") aborting ... ************ We've tried many things to debug it: * dbx Runtime Checking (RTC) is not detecting any (meaningful) memory access problems that I can see. * The same on Solaris/SPARC. * Neither does Valgrind on Linux. * I've tried increasing the C...

...mixed upper/lower case to define names. There is potential for using the capitalizations to make code more self explanatory, but only if a consistent system is used. In Java, capitalization is used to indicate the type of object. Names of methods are capitalized except for the first word (e.g., geneNames), names of classes are fully capitalized (e.g., ExprSet), names of data objects are all lowercase, and names of libraries have their own conventions but normally with lowercase letters. A programmer can recognize the type of object in many cases simply from the name. In R, Java capitalization...

Dear R-experts, I have a data file df as the following: genename variable at 1hr variable at 4 hr variable at 10 hr gene1 gene2 . . . gene5000 I would like to have a graph with X-axis as the time point (1hr, 4hr, 10hr), and Y-axis as the value of the variable. So, basically, I want to do a line with the three different values at 1hr , 4hr and 10hr for all the 5000 genes. My purpose is

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 False Called FDR 1 0.1 0.929 292.25 293 0.927 2 0.4 0.929 43.60 56 0....

...--vsize=2000M, but he still keeps saying it (needed 83Kb or some, more). I have tried to increase the heap memory to 2200M but he won't let me do it (too large and ignored). I used a 7 000 rows dataset. The commands I used are: > scan ("list_genes", what = "list") -> genenames > read.table(file ="list_signals", row.names = genenames) -> data > library (mva) > as.matrix(dist(data, method = "euclidean", diag = TRUE)) -> matrix > write.table(matrix, file = "euclidmartix") So here's my problem: maybe I can't use R (or...

...ata into R as follows: data <- read.delim("CD4PCR.txt",header=TRUE,row.names=1,sep="\t",dec=".",fill=TR UE) x<-as.matrix(data) dim(x) (11,37) =11 genes =37 samples (20 no disease, 17 disease) this code: set.seed(100) y <-c(rep(0,20),rep(1,17)) genenames<-as.character(data$Gene.Symbol) geneset<-as.character(rownames(x)) GSA.obj<-GSA.func(x,y, genenames, geneset, resp.type="Two class unpaired") returns this error: Error in 1:max(ngenes, na.rm = TRUE) : result would be too long a vector In addition: Warning message: In max(n...

...n 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 would like also to know what genes (NAMES) are included in each cluster. I tried unsuccessfully to send these results to output files (clusters with gene Names). This must be an easy task for a good R programmer. I will app...

...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, Mark heatmap(x = dataM, RowSideColors = RowSideColors, ColSideColors=ColSideColors, main = title, margins = c(50,50), scale= do.scale ,labRow=geneNames, labCol=colLabels, col = hmcol, cex.main = 1, cexRow = row.lab.mag, cexCol = col.lab.mag) > sessionInfo() R version 2.6.0 Under development (unstable) (2007-08-29 r42686) i686-pc-linux-gnu locale: LC_CTYPE=en_US.UTF-8;LC_NUMERIC=C;LC_TIME=en_US.UTF-8;LC_COLLATE=en_US.UTF-8;LC_MONE...

...lt;- matrix ( rnorm(1000*20), ncol=20 ) > dd <- sample ( 1:1000, size=100 ) > u <- matrix ( 2*rnorm(100), ncol=10, nrow=100 ) > x[dd,11:20] <- x[dd,11:20] + u > y <- c(rep(1,10),rep(2,10)) > > data <- list ( x=x, y=y, geneid=as.character(1:nrow(x)), + genenames=paste("g",as.character(1:nrow(x))) ) > > samr.obj <- samr ( data, resp.type="Two class unpaired", + nperms=100, logged2=TRUE ) Error in samr(data, resp.type = "Two class unpaired", nperms = 100, logged2 = TRUE) : unused argument(s) (logged...

...ad.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, geneid=as.character(normData[,1]),genenames=as.character(normData[,1]), logged2=TRUE) samr.obj<-samr(d, resp.type="Two class paired", nperms=100) delta.table <- samr.compute.delta.table(samr.obj) delta=0.4 siggenes.table<-samr.compute.siggenes.table(samr.obj,delta, d, delta.table,min.foldchange=2) genes.up <...

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 = list(x=A,y=y1,genenames=B,logged2=TRUE) testsamr <-samr(datasam,resp.type ="Two class unpaired",nperms=100) del <- 2 samr.plot(testsamr,delta) delta.table <- samr.co...

...rmdat))) return(list(mat,actclass)) } m <- makeColon() mat <- m[[1]] actclass <- m[[2]] mat <- matrix(as.numeric(mat),nrow(mat),ncol(mat)) geneid = as.character(1:nrow(mat)) gs = as.character(1:nrow(mat)) mydata <- list(x= mat,y=factor(actclass),geneid = geneid ,genenames=gs) mytrain <- pamr.train(mydata) new.scales <- pamr.adaptthresh(mytrain,ntries = 10, reduction.factor = 0.9) mytrain2 <- pamr.train(mydata,threshold.scale = new.scales) mycv <- pamr.cv(mytrain2,mydata,nfold = 10) res1 <- pamr.confusion(mycv, threshold...