similar to: heatmap.2 color issue

Hello R users, I'm trying to extract random samples from a big array I have. I have a data frame of over 40k lines and would like to produce around 50 random sample of around 200 lines each from this array. this is the matrix ID xxx_1c xxx__2c xxx__3c xxx__4c xxx__5T xxx__6T xxx__7T xxx__8T yyy_1c yyy_1c _2c 1 A_512 2.150295 2.681759 2.177138 2.142790 2.115344 2.013047

Dear sir/madam, I have been using R for a while now for microarray analysis, and I would like to make a "master" data frame in which I can combine information from many different sources. The basic list a genelist with 25.000 probes, then I would like to have a subcompartment with the statistical information, a subcompartment with more extensive information regarding each gene, and then

Hi, I have huge matrices in which the response variable is in the first column and the regressors are in the other columns. What I wanted to do now is something like this: #this is just to get an example-matrix DataMatrix <- rep(1,1000); Disturbance <- rnorm(900); DataMatrix[101:1000] <- DataMatrix[101:1000]+Disturbance; DataMatrix <- matrix(DataMatrix,ncol=10,nrow=100); #estimate

Hallo, > fit12<-lmFit(qrg[,1:2]) > t12<-toptable(fit12,adjust="fdr",number=25,genelist=qrg$genes[,1]) > t12 ID logFC t P.Value adj.P.Val B 522 PLAU_OP -6.836144 -8.420414 5.589416e-05 0.01212520 2.054965 1555 CD44_WIZ -6.569622 -8.227938 6.510169e-05 0.01212520 1.944046 Can anyone tell me what the difference is between P.Value

Hi, I have a question concerning the analysis of some affymetrix chips. I downloaded some of the data from GEO GSE11324 (see below). In doing so I'm stuck after I identified the probesets with significant changes. I have problems in assigning probeset specific gene names as well as getting the genomic coordinates. Furthermore I have no clue how to deal with the fact, that most genes have

Hi, I need to permute the rows of a matrix, where each row is independently rearranged. A simple solution is this: shuffled <- datamatrix <- matrix(1:24, ncol = 4) for (i in 1:nrow(datamatrix)) { shuffled[i, ] <- sample(datamatrix[i, ]) } > datamatrix [,1] [,2] [,3] [,4] [1,] 1 7 13 19 [2,] 2 8 14 20 [3,] 3 9 15 21 [4,] 4 10 16 22 [5,]

In datamatrix[, "y"] == datamatrix[, "y"][-1] : longer object length is not a multiple of shorter object length out = c(FALSE,datamatrix[,'y'] == datamatrix[,'y'][-1]) and I do not know why I get that error, the resulting out matrix is somehow one row larger than datamatrix... all I try to do is filter matrix by dropping rows where [,'y'][-1] ==

Hi. I have been looking at the PCAproj function in package pcaPP (R 2.4.1) for robust principal components, and I'm trying to interpret the results. I started with a data matrix of dimensions RxC (R is the number of rows / observations, C the number of columns / variables). PCAproj returns a list of class princomp, similar to the output of the function princomp. In a case where I can

I am having trouble converting the output from Sweave into a valid PDF file. I have created a simple .Rnw file which will become a full vignette at some point, but during the intermediate testing, I got errors from texi2dvi. This is what I have done. 0) Using a Windows Xp system 1) Created a file called GeneSpring.Rnw 2) Convert this to Tex using Sweave("GeneSpring.Rnw") from within R

Hi All, I have a 1000x1000000 matrix. The calculation I would like to do is actually very simple: for each row, calculate the frequency of a given pattern. For example, a toy dataset is as follows. Col1 Col2 Col3 Col4 01 02 02 00 => Freq of ?02? is 0.5 02 02 02 01 => Freq of ?02? is 0.75 00 02 01 01 ? My code is quite simple as the following to find the pattern ?02?.

Hello R users, I'm wondering whether it is possible to manage big data set in R? I have a data set with 3 million rows and 3 columns (X,Y,Z), where X is the group id. For each X, I need to run 2 regression on the submatrix. I used the function "split": datamatrix<-read.csv("datas.csv", header=F, sep=",") dim(datamatrix) # [1] 2980523 3

Hi list, I'm performing a series of confirmatory factor analysis on different groupings of items from data collected with questionnaires. There are some missing values. For those sets with no missing values I call factanal(datamatrix,factors=n) where datamatrix is a table of all observations for the items under investigation. This call fails when there are missing values. help(factanal)

Dear R users, I'am using marray and Limma packages to analyze genepix output. 1) how can I filter bad spots from my data (data contains 3 types of bad spots). my experiment contains 12 samples and the bad spot are not associated to the same probes 2) how can I remove control probes from my data ? I'm sorry, i'm new with R and I can't find answer in packages doc. best regards,

Hi, I am using 'igraph' to make some plots. The problem I got is that I don't know how to label the nodes with gene names. My sample code: ## suppose I have 100 gene (nodes) ## --------------------------------------------------------------------------- graph <- set.vertex.attribute(graph, "color", value=c(rep(c('green','red'),50))) graph <-

I have 2 mysql tables, Product and Color: Color ID ColorName 1 Red 2 Green 3 Yellow 4 Blue Products ID Color1 Color2 Color3 ProductName 1 ? ? ? Orco 2 ? ? ? Skeletor 3 ? ? ? He-Man I need to display the ColorName to

Hi, Here in R, I need to load a huge file(.csv) , its size is 200MB. [may come more than 1GB sometimes]. When i tried to load into a variable it taking too much of time and after that when i do cbind by groups, getting an error like this " Error: cannot allocate vector of size 82.4 Mb " My requirement is, spilt data from Huge-size-file(.csv) to no. of small csv files. Here i will give

Hi all, I am wandering.. is it possible to cluster data which is in a single column ? for example.. I have some data as follows: 4013 7362 7585 9304 11879 14785 21795 30500 30669 30924 33988 36975 40422 42911 50501 51593 53729 54338 55497 57337 61993 62601 66229 69815 69933 70760 71340 75921 83972 90134 91061 . . . is it possible to cluster this data since it is in a single column ? I have

hi I want to compare two list by its names and get the values of that list. can anybody let me know the syntax of comparing the list by their names using a for loop c.genes<- list() for(i in 1:100) c.genes[[1]]<- geneset(which(geneset == tobecampared[i])) } here geneset is a list and also tobecampared is a list Thank you Ramya -- View this message in context:

Hi here i have a code to split a csv file as per group of line. The code given below, ------------------------------------ SplitCSVByLine <- function(DataMatrix,Destination,NoOfLineToGroup) { input <- file(DataMatrix, "r") fileNo <- 1 repeat { myLines <- readLines(input, n=NoOfLineToGroup) if (length(myLines) == 0) break

Hallo, how can I store a variable as a tab-delimited txt-file? I crated a variable with the following commands: > fit12<-lmFit(qrg[,1:2]) > t12<-toptable(fit12,adjust="fdr",number=25,genelist=qrg$genes[,1]) > t12 ID logFC t P.Value adj.P.Val B 522 PLAU_OP -6.836144 -8.420414 5.589416e-05 0.01212520 2.054965 1555 CD44_WIZ -6.569622