search for: geneid

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 for small datasets, but as I am working with around 30,000 entries, it proved too slow and I'm not sure how to do it in another way. Here is an example...

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...

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 MethodID in any particular order and, in fact, there doesn't need t...

...odes, I attempt to convert the data.frame into a matrix. However I notice that data.matrix function doesn't seem to work. __ BEGIN__ dat <- read.table("mydata", comment.char = "!" , na.strings = "null"); # Select n-genes by random sample # n = 1 nosamp <- 1 geneid <- sequence(nrow(dat)) geneid.samp <- sample(geneid,nosamp) geneid.samp gexp<- dat[geneid.samp,] gexp.arr <- data.matrix(gexp, rownames.force = NA) print(is.matrix(gexp.arr)) print(gexp.arr) __END__ Yielding this output: __BEGIN__ > print(is.matrix(gexp.arr)) [1] TRUE > prin...

...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),"\\.") > Rumino_Reps_agreeWalignTR<-transform(Rumino_Reps_agreeWalign,taxid=do.call(rbind, strsplit)) Warning message: In function (..., deparse.level = 1) : number of columns of result is not a multiple of vector length (arg 1) here is my data: > head(Rumino_Reps_agr...

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 1007_s_at:1105:483 0 0 DDR1 780 21 6 + 30975403 30975427 2 1007...

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 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 1007_s_at:1105:483 0 0 DDR1 780 21 6 + 30975403 30975427 2 1007...

...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. 3.cox[,'endpoint'])~pcc.primary.stg.3.cox[,'geneid'],pcc.primary.stg.3.cox) each time I tried to look at what is in survtest it gives me this: ============================================================================ ============== coxph(formula = Surv(pcc.primary.stg.3.cox[, "fup_interval"], pcc.primary.stg.3.cox[, "...

...dat <- normdat[-1,] mat <- as.matrix(cbind(cancdat,normdat)) actclass <- rep(c(1, 2), c(ncol(cancdat), ncol(normdat))) 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(myda...

...;- normdat[-1,] mat <- as.matrix(cbind(cancdat,normdat)) actclass <- rep(c(1, 2), c(ncol(cancdat), ncol(normdat))) 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...

...dat <- normdat[-1,] mat <- as.matrix(cbind(cancdat,normdat)) actclass <- rep(c(1, 2), c(ncol(cancdat), ncol(normdat))) 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(myda...

Dear cateGOry experts, hyperGTest documentation states that YEAST cannot be used as 'annotation' when evaluating gene ontology representation status for a given set of 'geneIds'. Because I am using a custom print I believe I need to create my own data package to use as the annotation file for 'annotation'. Can someone please describe how to make a data package that will be compatible with the 'annotation' required for proper function of hyperGTest?...

R-users, I have the following piece of code which I am trying to run on a dataframe (aga2) with about a half million records.  While the code works, it is extremely slow.  I've read some of the help archives indicating that I should allocate space to the p1 and ags1 vectors, which I have done, but this doesn't seem to improve speed much.  Would anyone be able to provide me with advice on

...he man pages ... > > set.seed(100) > x <- 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 =...

...ve 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) pValueTime<-matrix(nrow=B,ncol=2) colnames(pValueTime)<-c('geneID','pValue.Time') for (i in 1:B) { print(i) gene = teste$gene [i] keep<-teste$gene==gene MTemp =as.numeric( teste$M [keep]) timeTemp = as.factor(teste$time [keep]) animalTemp = as....

...ette()'. To cite Bioconductor, see 'citation("Biobase")' and for packages 'citation(pkgname)'. Loading required package: AnnotationDbi Loading required package: DBI Loading required package: RSQLite An object of class "GeneSetCollection" [[1]] setName: NA geneIds: X (total: 1) geneIdType: Null collectionType: Null details: use 'details(object)' Actually, the behavior is more complicate than appears; in a new R session after loading /tmp/x.Rda, if I immediately do x[[1]] I get the show,GeneSetCollection-method but not show,GeneSet-method. Sorry...

...rk 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, 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,...

Dear Listers: Currently I am doing a research using a microarray data. I have two questions and hope I can get some help from here: 1. I have a dataset like the following, in which V1 is geneid, v3...are the fold changes of expression levels for different patients. There are multiple probes for one gene, so there are multiple rows. You can see from column V11 and V13, the fold changes are very different. Is it very common in microarray data analysis? Generally how to deal with that? I don...

I'm running samr (Two class unpaired), but keep getting the following error: perm= 1 Error in if (logged2) { : argument is of length zero <code> library (impute) library (samr) data = list (x=dat, y=y, geneid = matrix(twoUnpaired.data[,1],ncol=1), genenames = matrix(twoUnpaired.data[,2], ncol=1)) samr.obj <- samr (data, resp.type="Two class unpaired", nperms=100) </code> Would someone please shed some light. Thank you. [[alternative HTML version deleted]]