similar to: How to calculate correlation matrix for 128 * 12625 matrix

Transpose vector extracted from a matrix Hello, I am doing a recursive analysis that uses every line (vector) of a matrix in a loop. In the model, I need to transpose those vectors that are extracted from a matrix. Using simple vectors (no matrix involved) the transpose function works fine: simplevector <-matrix(1:3,3,1) tsimplevector <-t(simplevector) #transposed dim(simplevector)

Dear All, I have a file (a matrix) on which I have to compute the correlations. The function "cov" compute the correlations between the columns of a matrix, but I want to compute the correlations between the raws. Can somebody say to me how I can carry out that? Thanks Laurence -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list --

Hi, I am a newbie to the world of R. I have a data converted in csv format. Few cells in some of the rows of the data are blank ( in the sense that there is no value available for the particular experiment). When i try to open the file in R. I get an warning message. The specific warning message i get is {Warning message: NAs introduced by coercion } My data more or less looks like this -

x <- read.table("LittleGarvin.csv", sep=",", header=TRUE) y <- t(x) str(y) chr [1:193, 1:288] "oligocha" "0" " 0" " 0" " 0" "0" ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:193] "X" "upwd1201" "upwd0502" "upwd0702" ... ..$ : NULL x is a data frame with

Dear All, It's Eszter from Hungary, a total beginner with R. My problem is the following: I have a dataset with binary values as a comma separated textfile. The samples are in the coloumns and the species are in the rows. I have to transpose it for the further PCoA analysis. There is no problem with reading the dataset. When I transpose the dataset, the original values become

Given a matrix of m*n, I want to reorder it as a vector, using a row major transpose. so: > m<-matrix(seq(1,48),nrow=6,byrow=T) > m [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 1 2 3 4 5 6 7 8 [2,] 9 10 11 12 13 14 15 16 [3,] 17 18 19 20 21 22 23 24 [4,] 25 26 27 28 29 30 31 32 [5,] 33 34 35 36 37

Dear All, I am not familiar with R yet I want to use it to perform some task, hence my posting here. I hope someone can help. I have a set of data, genes (rows) and samples (columns). I want to do a Pearson correlation on all the possible pairwise combinations of all the genes (2000). Does anyone have an idea of how to execute this in R? Thanks in advance. -- View this message in context:

Hi, I'm trying to write a function to determine the euclidean distance between x (one point) and y (a set of n points). How should I pass y to the function? Until now, I used a matrix like that: | [,1] [,2] [,3] [1,] 0 2 1 [2,] 1 1 1 | Which would pass the points (0,2,1) and (1,1,1) to that function. However, when I pass x as a normal (column) vector,

Hello All, I was wondering if it's possible to reshape data from long to wide in R without using a "timevar". I've pasted some sample data below along with some code. The data are sorted by Subject and Drug. I want to transpose the Drug variable into multiple columns in alphabetical order. My data have a variable called "RowNo" that functions almost like a

Hi, suppose I have following codes : library(zoo); library(ggplot2) dat <- matrix(rnorm(500*2), 500); dat <- zooreg(dat, start = as.Date("01/01/01", "%m/%d/%y"), frequency=1); plot(dat) head(dat); month.no <- format(index(dat), "%m"); dat1 <- cbind(coredata(dat), as.numeric(month.no)) x <- dat1[,1]; y <- dat1[,2]; z <- dat1[,3] Now I draw a

Hi folks, I want to sort a matrix row-by-row and create a new matrix that contains the corresponding colnames of the original matrix. E.g. > set.seed(123) > a <- matrix(rnorm(20), ncol=4); colnames(a) <- c("A","B","C","D") > a A B C D [1,] -0.56047565 1.7150650 1.2240818 1.7869131 [2,]

Dear list, We have a number of files containing similarly structured data: file1: A B C 1 2 3 4 5 6 file2: A B C 7 8 9 10 11 12 ... etc My part of R receives all these data as an array: 1,2,3... 12 together with info about dimensions (row,col,fileN) . ( Converting the data into 3D cannot simply done by: array(x, c(2,3,2)) because breaks the structure (e.g. 1,3,5 is type mismatch)

Hi! I have tried to install dovecot as my imap service on my FreeBSD server. At first all looked fine and worked flawless. But after a while i started to get errors. The imap process dies with signal 12 when the client tries to check the contens of the folder. dovecot: Apr 07 09:55:17 Error: child 12625 (imap) killed with signal 12 Any ideas what may cause this problem? MvH Johan Willard

Hi, I have a test_table where the dim is 62220 by 73 (row by col) I would like to partition the rows into 170 equal parts (170 tables where each is of dim 366 by 73), and rearrange them horizontally. The source codes I have: for (i in 1:170) { c = cbind(c,test_table[(367*i+1):(367*(i+1)),2:73]); } Unfortunately, using for loop and cbind for a table of this size

Hi all, if I transpose a matrix with t(data), the newly created colums do not appear to have the first row as header. How can I do to have all the newly created columns have their first row as a header? Thanks Gabriele Zoppoli, MD Ph.D. Fellow, Experimental and Clinical Oncology and Hematology, University of Genova, Genova, Italy Guest Researcher, LMP, NCI, NIH, Bethesda MD Work: 301-451-8575

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

Undoubtedly this question has been asked before, I just can't seem to find the combination of search terms to produce it. I'm trying to resize a dataset that is pulled into R using read.table. However, I think the same problem can be produced using matrix: x<-matrix(1:64,8) x # [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] #[1,] 1 9 17 25 33 41 49 57 #[2,] 2 10

Hello, Sorry. It may be a stupid question. I have two vectors a<-c(9,3,5) b<-c(3,4,1) How can I get the variance-covariance matrix of these two vectors? I tried cov(a,b), I got a number not a matrix. I tried to transpose vector a and b as t(a) and t(b), it still cannot work. Any suggestions? Thank a lot! -- View this message in context:

I use a large real matrix, X, in C code that is passed from R and transposed in place in the C code. I would like to conserve memory and, if possible, allocate space for only one copy of X -- hence I would like to pass a pointer to the data in the X object to the C code. The Writing R Extensions manual says that neither .Call nor .External copy their arguments. They also say that these

I am currently trying to write a program that minimises the amount of work required for “auditable” qPCR data. At the moment I am using an Excel (.csv) spreadsheet as source data that has been transposed to the column format required for R to read. Unfortunately, this means I have* *to manually confirm the whole data set prior to doing any analysis, which is taking a considerable amount of time!