similar to: Reordering the correlation matrix

Dear All, I have a matrix of size 10000 x 50. I would like to calculate all possible pair-wise correlation coefficient (5x10^7 combinations) using cor(). How can I efficiently calcualte and save the result in a matrix? Thanks in advance. Kind regards, Ezhil

Dear All, I have a correlation matrix of size 100 x 100 and would like to extract the diagonal matrix from it. I have used the for loop to store tha correlation values of the diagonal matrix. Is there a 'R way' of doing this? Thanks in advance. Kind regards, Ezhil

Hi! All, To find co-expressed genes from a expression matrix of dimension (9275 X 569), I used rcorr function from library(Hmisc) to calculate pearson correlation coefficient (PCC) and their corresponding p-values. From the correlation matrix (9275 X 9275) and pvalue matrix (9275 X 9275) obtained using rcorr function, I wanted to select those pairs whose PCC's are above 0.8 cut-off and then

Dear All, I have two matrices A (40 x 732) and B (40 x 1230) and would like to calculate correlation between them.  I can use: cor(A,B, method="pearson") to calculate correlation between all possible pairs. But the issue is that there is one-many specific mappings between A and B and I just need to calculate correlations for those pairs (not all). Some variables in A (proteins, say p1)

Dear All, I have a correlation matrix say 'M' (4000x4000) for 4000 genes and I want to subset it to 'N' (190x190) for 190 genes. The list of those 190 genes are in variable 't'. So the idea is to read the names of genes from variable 't' and subset the matrix M accordingly. Any thoughts are welcome! Best Lee [[alternative HTML version deleted]]

In our dataset the samples/object are number of patients which is 128 and we are dealing with 12,625 genes which is our attributes of the dataset. So, it is obvious that if I calculate the correlation matrix of (128 * 12,625) the resulted dimension of the correlation matrix will be (12,625 * 12,625). I need some help about this calculation. 1. How I can make the transpose matrix of 12625 * 128

Hello, I am new to R and have a problem I have had some trouble with. Basically I have a list of some 80000 genes or so with data points for expression levels at various time points/conditions. I also have subsets of these, usually only a few hundred genes in size, known to be associated with some biological process. What I want to do is correlate the entire list with my subset and then

Dear Ioannis Thank you very much for pointing me to meta-analysis. Although it may not solve my problem with the normalization, it gives me some other options to display the different correlation coefficients. One possibility is the use of Funnel plots, which are even available in library(rmeta). Another possibility is the use of forest-plots, as implemented in rmeta as metaplot. Sorrowly,

Dear All, I have large matrix (46000 x 11250). I would like to do the linear regression for each row. I wrote a simple function that has lm() and used apply(mat,1,func). The issue is that it takes ages to load the file and also to finish the lm. I am using LINUX 64 bit with 32G mem. Is there an elegant and fast way of completing this task? Thanks in advance. Kind regards, Ezhil

Dear all, I need some help on matrix design and B statistics by using limma package. I want to compare gene expression in 2 groups of cDNA samples. The experiment compares 4 treated mice(#1,#2,#3,#4) and 4 control mice (#5,#6,#7,#8). The target file is FileName Cy3 Cy5 mice1.spot Control_#5 Treat_#1 mice2.spot Treat_#1 Control_#5 mice3.spot Control_#6 Treat_#2

Dear all I apologize for cross-posting, but first it is accepted custom to thank the repliers and give a summary, and second I have still the feeling that this problem might be a general statistical problem and not necessarily related to microarrays only, but I might be wrong. First, I want to thank Robert Gentleman, Mark Kimpel and Mark Reiners for their kind replies. Robert Gentleman kindly

Dear list members, I have been using R to create a heatmap where my data has continous variables from 0 to 100. When I create the heatmap, although the branches are correct, they do not order themselves so that the row with the most zeros is at one end and the row with the most 100s is at the other, which is what I would like them to do, so as to create a colour gradient down the graphic. I have

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

Hi everyone, I am new to R-project. I did search through the list for my problem but i can't find it. I am sorry if this question has been asked. I would like to perform a correlation analysis between a hiv data and gene expression. Basically, i have a file that contains: hiv_name, start_position, end_position, chromosome. I would like to see if these data has anything to do with the

Hi All I have a symmetric matrix of genes ( 100x100 matrix). I also have a matrix (100x2) of two columns where column 1 has the gene names and column 2 has the cluster it belongs to (they are sorted and grouped based on the cluster no). I would like to order the rows and columns of the 100x 100 matrix such that the first n genes correspond to cluster 1 and next n genes correspond to cluster 2

Hello all, I have a set of microarray timeseries (approx. 18000 genes and 7 time points per gene) data that I have correlated with a template (a vector of length 7). I have also correlated random data from a normal distribution with the same mean and standard deviation as my data set with the template, as well as, correlating a random permutation of my data set with the template. So I now

Dear All, I have an exon array and did not find any differential gene expression between two samples. I was looking to perform correlation analysis on the same. Can anyone recommend any package that would do this for an affy exon array? Will SAM analysis give me correlated genes? Thanks and regards, Ekta The information contained in this electronic message and in any attachments to this message

Hi r-help community, This question isn't so much a syntax/coding one, but here goes: Let's say I have matrix of arbitrary dimensions and I'd like to reorder the rows in such a way that I could maximize the sum of the entries along the diagonal. For example, for this 3x3 matrix: [,1] [,2] [,3] [1,] 3 4 13 [2,] 9 1 2 [3,] 2 11 1 rearranging the rows

Hi, I have a matrix HR(9x27). I would like to make a single vector with elements: t(HR[,1]) followed by t(HR[,2]) and then t(HR[,3] ... etc. Is there any neat way of converting this matrix into a vector rather doing something like c(t(HR[,1]), t(HR[,2]), t(HR[,3]) ..)? Thanks in Advance. Kind regards, Ezhil ____________________________________________________________________________________

Hello All, I have a panel date - here a small-scale example: df <- data.frame(cbind(rep(c("AUT","BEL","DEN","GER"),4),cbind(rep(c(1999,2000,2001,2002),4)),sample(10,16,replace=T))) names(df) <- c("country","year","x") SORT <- c("GER","BEL","DEN","AUT") I need to compute the