similar to: mt.plot...

Hello, I'm apologize to have made failure before. I wrote this : p<-scan("teststat.txt") on R and R returns Error in scan ("teststat.txt") : "scan" expected a real, got "x". I don't really understand,because teststat has been created, so........ Thanks a lot. Sandrine

We are happy to announce that the second R user conference useR! 2006 is scheduled for June 15-17 2006 and will take place at the Vienna University of Economics and Business Administration. This second world-meeting of the R user community will focus on - R as the `lingua franca' of data analysis and statistical computing, - providing a platform for R users to

We are happy to announce that the second R user conference useR! 2006 is scheduled for June 15-17 2006 and will take place at the Vienna University of Economics and Business Administration. This second world-meeting of the R user community will focus on - R as the `lingua franca' of data analysis and statistical computing, - providing a platform for R users to

The Bioconductor core group would like to announce the 1.3 release of the Bioconductor software. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to check them out. Release 1.3 is intended to be operated with R version 1.8.X, which can be obtained at CRAN (http://cran.r-project.org/) -- WHAT FEATURES DOES THIS RELEASE PROVIDE?

The Bioconductor core group would like to announce the 1.3 release of the Bioconductor software. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to check them out. Release 1.3 is intended to be operated with R version 1.8.X, which can be obtained at CRAN (http://cran.r-project.org/) -- WHAT FEATURES DOES THIS RELEASE PROVIDE?

Greetings! The Bioconductor core group would like to announce the 5th release of Bioconductor, version 1.4. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to upgrade existing tools and check out the new packages. Release 1.4 is intended to be operated with R version 1.9.x, which can be obtained at CRAN

The Bioconductor development team announces release 1.1 of the Bioconductor packages for the analysis of genomic data. Bioconductor is an open source bioinformatics software project based on R. Version 1.1 features: ===================== * All packages from the 1.0 release are included. All current bug fixes have been applied, and most have upgraded and provide enhanced functionality. *

The Bioconductor development team announces release 1.1 of the Bioconductor packages for the analysis of genomic data. Bioconductor is an open source bioinformatics software project based on R. Version 1.1 features: ===================== * All packages from the 1.0 release are included. All current bug fixes have been applied, and most have upgraded and provide enhanced functionality. *

The Bioconductor development team announces release 1.2 of the Bioconductor packages for the analysis of genomic data. Bioconductor is an open source bioinformatics software project based on the R language. Version 1.2 features: ===================== * All packages from the 1.1 release are included. All current bug fixes have been applied, and most have been upgraded and provide enhanced

Dear R community I sent a message out a while ago asking for help with multiple comparison tests for ANOVA's, but haven't had any response yet. I'm sending a final desperate plea. If I can't get this done in R I'm going to have to redo a whole lot of stuff in a commercial package, which I'm REALLY not keen to do! My problem is how to implement these tests in R. Below

dear all, I recently came across the following issue and I was not sure whether it is intentionally or not: using p.adjust to adjust p-values for multiple hypothesis testing using the method from Benjamini and Hochberg removes all NA values from the input vector and does not account for them in the adjustment, i.e. in a vector of 23 p-values with 20 of them being NA it adjusts the 3 non-NA

The Partek package (www.partek.com) allows only two selections for Multiple Test Correction: Bonferroni and Dunn-Sidak. Can anyone suggest why Partek implemented Dunn-Sidak and not the other methods that R has? Is there any particular advantage to the Dunn-Sidak method? R knows about these methods (in R 2.1.1): > p.adjust.methods [1] "holm" "hochberg" "hommel"

Hi, I have two questions want to ask. 1. If I have a matrix like this, and I want to figure out the rows whose value in the 3rd column are less than 0.05. How can I do it with R. hsa-let-7a--MBTD1 0.528239197 2.41E-05 hsa-let-7a--APOBEC1 0.507869409 5.51E-05 hsa-let-7a--PAPOLA 0.470451884 0.000221774 hsa-let-7a--NF2 0.469280186 0.000231065 hsa-let-7a--SLC17A5

Full_Name: Ludo Pagie Version: 2.8.1 OS: linux Submission from: (NULL) (194.171.7.39) p.adjust in stats seems to have a bug in handling n>length(p) for (at least) the methods 'holm' and 'hochberg'. For method 'holm' the relevant code: i <- 1:n o <- order(p) ro <- order(o) pmin(1, cummax((n - i + 1) * p[o]))[ro] where p is the

Hi, I have to deal with a huge .txt table (~485.577 rows and 469 columns, > 1.5 Go file) I used the read.table function > tmp=read.table("data.txt", header=TRUE, sep="\t", fill=TRUE, na.strings="NA", comment.char="", stringsAsFactors = FALSE) However, I encounter troubles in interpreting some "\t" separator.. A column displays \t\t\t\t

I append below a suggested update for p.adjust(). 1. A new method "yh" for control of FDR is included which is valid for any dependency structure. Reference is Benjamini, Y., and Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Annals of Statistics 29, 1165-1188. 2. I've re-named the "fdr" method to "bh" but

I am posting this to both R and BioC communities because I believe there is a lot of confusion on this topic in both communities (having searched the mail archives of both) and I am hoping that someone will have information that can be shared with both communities. I have seen countless questions on the BioC list regarding limma (Bioconductor) and its calculation of FDR. Some of them involved

I am posting this to both R and BioC communities because I believe there is a lot of confusion on this topic in both communities (having searched the mail archives of both) and I am hoping that someone will have information that can be shared with both communities. I have seen countless questions on the BioC list regarding limma (Bioconductor) and its calculation of FDR. Some of them involved

Hello, I am trying to use the p.adjust function for multiple testing. here is what i have 9997 201674_s_at 0.327547396 9998 221013_s_at 0.834211067 9999 221685_s_at 0.185099475 I import them from excel have have the gene symbol as well as the pvalue here is the issue > pa<-p.adjust(pt,method="BH") Error in p[nna] : object is not

Hi, I am studying Kalman Filter and it seems to be difficult for me to apply the filter on a simple ARMA. It is easy to construct the state-space model, for instance: dlmModARMA(ar=c(0.4,-0.2),ma=c(0.2,-0.1, sigma2=1) but applying the dlmFilter on it, it doesn't work... I don't know if my problem is clear but if anyone has already worked on Kalman filter, it could be great to advise me!