similar to: Help on selecting genes showing highest variance

Hello All, I need your help. I am analysing affymetrix data and have to select the probe-set that has median expression among all the probe-sets for same gene. This way I want to remove the redundancy by keeping the analysis to single gene entry level. I am fully aware that it is not a nice thing to do but I just have to do it. To do so, I came across 'findLargest' function of

Hello! I am aggregating using a formula in aggregate - of the type: aggregate(cbind(var1,var2,var3)~factor1+factor2,sum,data=mydata) However, I actually have an object (vector of my variables to be aggregated): myvars<-c("var1","var2","var3") I'd like my aggregate formula (its "cbind" part) to be able to use my "myvars" object. Is it

Hello ... I've noticed that some of our Bioconductor code was running drastically slower under current R-devel vs. current R-patched - one example is below using a ttest. I have the following snippet of code that demonstrates the problem while avoiding "real" code that takes an extremely long time to finish on R-devel: library(genefilter) data(eset) eset$cov1 z <-

Hi How do I install "gregmisc" packages? I did- % sudo R > install.packages("gregmisc") . . > barplot2() but, Error: couldn't find function "barplot2" -- atuya Mac OSX 10.2.6 R 1.7.1

All, I believe I am running the latest version of rshape2 (1.2.1). But this code: library(reshape2) tmp <- melt(smiths, id.vars=1:2, measure.vars=c("age","weight","height"), variable.name="myvars", value.name="myvals" ) names(tmp) Produces this output: > names(tmp) [1] "subject" "time"

Hi All, i have searched the web for a simple solution but have been unable to find one. Can anyone recommend a neat way of deleting multiple variable? I see, i need to use dataframe$VAR<-NULL to get rid of one variable, In my situation i need to delete all vars between two points. I've used the 'which' function to find these out and have assigned to myvar >myvars [1] 2 17 but

A package uses VignetteEngine: knitr; the package itself does not Suggests: knitr, but it Suggests: BiocStyle which in turn Suggests: knitr. Nonetheless, R CMD check fails indicating that a package required for checking is not declared. Is it really the intention that the original package duplicate Suggests: knitr? This is only with a recent R. In detail, with $ Rdev --version|head -3 R Under

Hello! I have a data set: set.seed(123) y<-data.frame(week=seq(as.Date("2010-01-03"), as.Date("2011-01-31"),by="week")) y$var1<-c(1,2,3,round(rnorm(54),1)) y$var2<-c(10,20,30,round(rnorm(54),1)) # All I need is to create lagged variables for var1 and var2. I looked around a bit and found several ways of doing it. They all seem quite complicated - while in

Hi, I discover that when I save a workspace containing a genefilter (pkg from Bioconductor) object I cannot open no more after. I have to restore the .RData file from a backup to be able to start R again. I didn't upgrade to Version 2.2 but I'm not sure that it will solve the problem. Did anyone have encounter the same problem? Below is a short r session to reproduce the error: ...

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Hello, I am trying to make a heatmap in R and am having some trouble. I am very new to the world of R, but have been told that what I am trying to do should be possible. I want to make a heat map that looks like a gene expression heatmap (see http://en.wikipedia.org/wiki/Heat_map). I have 43 samples and 900 genes (yes I know this will be a huge map). I also have copy numbers associated with

Hello, I am trying to run R on my Mac (OS10.5.6) and am having trouble installing and running packages (genefilter in particular in Bioconductor) I've tried re-installing R and it hasn't solved the issue. Thanks, ~Nicole Slusher

Dear R gurus, I have a very embarrassingly parallelizable job that I am trying to speed up with snow on our local cluster. Basically, I am doing ~50,000 t.test for a series of micro-array experiments, one gene at a time. Thus, I can easily spread the load across multiple processors and nodes. So, I have a master list object that tells me what rows to pick up for each genes to do the t.test from

Hi, R-help group, I kinda meeting a question when using R-2.12.0(Previous version is 2.10.0): When I typed "library("Biobase")", everything is alright! But when I type "library("genefilter")", it doesn't work! And echo this: Error in library.dynam(lib, package, package.lib) : DLL 'RSQLite' not found: maybe not installed for this

Dear R list, I think my question maybe easy for you but I really spent entire day to resolve it. Say I have a matrix, rows are 6000 genes, columns(1-6) are 3 genotypes (a,b,c) with 2 repeat. I have to use two groups each time for t-test, a vs. c or b vs. c, but I dont know how to write correct codes. Below is my codes, the last two lines are needed to be corrected....

I am so happy about learning how to read in multiple Excel files, that I have to try and make another improvement. I know what I have been doing is clumsy, but it works. Hopefully, someone can suggest a more elegant solution. As a novice, I have been using MS-Word and mail merge to write my code. I start with about 2 pages of code, and end up with 2,220 merged pages that I copy and paste into R.

Hi, I am relatively new to R and Bioconductor and am trying to filter the topTable that I generated of differentially expressed genes from my normlized eset file comprised of ~ 40 HG-133A Affy microarrays . I would like to see if particular probesets are represented in this list. Alternatively I would like to generate a topTable of differentially expressed genes using only specified probesets

Hello everyone, I have a data frame (tt), see below (I only show 2 genes, actually I have a lot): group gene1 gene2 Control 28.9776 9.9355 Control 28.9499 10.0997 Control 29.5468 14.2995 Control 29.5246 13.9561 Test1 29.1864 9.7718 Test1 29.2048 10.0388 Test1 34.9563 11.9509 Test1 34.9464 11.8909 Test2 36.9566 14.5316 Test2 37.1309 14.5188 Test2 36.1017

I am in need of someone's help in correlating gene expression. I'm somewhat new to R, and can't seem to find anyone local to help me with what I think is a simple problem. I need to obtain pearson and spearman correlation coefficients, and corresponding p-values for all of the genes in my dataset that correlate to one specific gene of interest. I'm working with mouse Affymetrix

Hello, I am running cluster analysis, and am attempting to create a graph of my clusters. I keep on getting an error that says that my figure margins are too large. d <- file.choose() d <- read.csv(d,header=TRUE) mydataS <- scale(d, center = TRUE, scale=TRUE) #Converts mydataS from a matrix to a data frame mydataS2 <- as.data.frame(mydataS) #removes "coden"