similar to: Significance Test for Correlation Coefficients

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 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, I am trying to perform a significance analysis of a microarray experiment with survival data using the {samr} package. I have a matrix containing my data which has 17816 rows corresponding to genes, and 286 columns corresponding to samples. The name of this matrix is data.matrix2. Some of the first values of this matrix are: data.matrix2[1:3,1:5] GSM36777 GSM36778 GSM36779

Hello R-community, It's been a week now that I am struggling with the implementation of a cox model in R. I have 80 cancer patients, so 80 time measurements and 80 relapse or no measurements (respective to censor, 1 if relapsed over the examined period, 0 if not). My microarray data contain around 18000 genes. So I have the expressions of 18000 genes in each of the 80 tumors (matrix

Hi, R! Question1: I am trying to correlate two vectors of numbers (two columns of microarray signal values) by using the non-parametric Spearman's rank correlation coefficient rho: > cor.test(V2.Signal,V3.Signal,method="spearman") but I get the error message: Error in if (q > (n^3 - n)/6) pspearman(q - 1, n, lower.tail = FALSE) else pspearman(q, : missing value

I estimated spearman's correlation coefficient using cor(). How do I test for significance? Vikas

Hi, May be this helps: ?set.seed(24) ?mydata4<- as.data.frame(matrix(sample(1:100,10*38,replace=TRUE),ncol=38)) ?dim(mydata4) #[1] 10 38 ?library(matrixStats) res<-do.call(cbind,lapply(1:400, function(i) {permutation<-sample(mydata4); (rowMeans(permutation[,1:27])-rowMeans(permutation[,28:38]))/(rowSds(permutation[,1:27])+rowSds(permutation[,28:38]))} )) ?dim(res) #[1]? 10 400 A.K.

Hi, based on the sample size I want to calculate whether to correlation coefficients are significantly different or not. I know that as a first step both coefficients have to be converted to z values using fisher's z transformation. I have done this already but I dont know how to further proceed from there. unlike for correlation coefficients I know that the difference for z values is

[Apologies in advance if this is too "statistics" and not enough "R".] I've got an experiment with two sets of treatments. Each subject either received all treatments from set A or all treatments from set B. I can compute the N pairwise correlations for all treatments in either set using cor(). If I take the mean of these N pairwise correlations, I see that the effects

How can I subscribe to R genomic list? On Sun, 2 Apr 2023, 9:28 pm Peter Langfelder, <peter.langfelder at gmail.com> wrote: > It's a microarray data set, so I don't think you would want to apply > an RNA-seq pipeline. You'd be better off applying a normalization > appropriate for this type of microarray data. > > HTH, > > Peter > > On Sun, Apr 2, 2023

It's a microarray data set, so I don't think you would want to apply an RNA-seq pipeline. You'd be better off applying a normalization appropriate for this type of microarray data. HTH, Peter On Sun, Apr 2, 2023 at 11:09?PM Anas Jamshed <anasjamshed1994 at gmail.com> wrote: > > I want to get the count matrix of genes from >

Dear R users, There is a error message when I run the following code. It is used to load microarray data and use the top 1000 genes for training svm to classify test set . > library(e1071) Loading required package: class > f=read.table("F:\\lab\\ microarray analysis\\VEH LPS\\exprs.txt",

Hi, I am performing Cox proportional hazards regression on a microarray dataset with 15000 genes. The p values generated from the Cox regression (based on normal distribution of large sample theory) showed only 2 genes have a p value less than 0.05. However, when I did a permutation on the dataset to obtained permutated p values, and it turned out about 750 genes had a permutated p value less than

Hi, I'm running a tutorial ("Meta-analyses of data from two (or more) microarray data sets"), which use wgcna package. I have an error in the function modulePreservation (it is below). I'm using R2.13 Can you help me? Do you know, what is happens? Thanks Raquel multiExpr = list(A = list(data=t(badea)),B = list(data=t(mayo))) # two independent datasets (dim = 13447 x 36) mp =

I am currently using the coxph function from R on a microarray dataset. The curve fit is performed using each gene's expression measurements separately. I then get a p-value for each gene, from the Coxph.summary method. Can someone please explain how this is computed and the significance of the p-value? However, the bigger question I have is how to perform permutation tests to get a

>Date: Thu, 6 Mar 2008 06:46:07 -0800 (PST) >From: Keizer_71 <christophe.lo@gmail.com> >Subject: [R] Statistical Questions: finding differentially expressed >genes >To: r-help@r-project.org >Message-ID: <15873163.post@talk.nabble.com> >Content-Type: text/plain; charset=us-ascii >Hi Everyone, >I am trying to find a way to do this in excel to tell me which

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

Hi All, I want to select rows at random from a large data.frame while achieving a particular distribution defined my a given subset of this data.frame. How can I do this? More details and what I've done so far is given below. I have gene expression data and gene sets of interest. In order to look at enrichment of differential expression I'm doing a simple permutation approach: Selecting

Dear R users, I am sorry to disturb you! But I really need your help for the usage of sigPathwy. Actually, I want a sliding window analysis for possible chromosome expression pattern mining. My research microorganism is a plant pathogen, Gibberella zeae, and I first used SAS to divide locus number with 10, 20, 30, or 40 on the fungal chromosome according to their location. I really

Hallo, I just installed all needed packages for my project on my PC. But I cannot load all at one time. I now want to load limma. How can I realize the following plan: I want to install for example limma inclusive all needed other sub packages (add-on). Can anyone tell me the corresponding command? Thanks, Corinna Here is the result of the command library(): Pakete in Library