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Hi everybody, I have a problem when trying to do the quality control with the packages simpleaffy and affyQCReport with the drosophila chip 2.0 At first I got the messeage, that the *.qcdef file is not there. I followed the instructions in tha manual and created the file like that: array drosophila2cdf alpha1 0.05 alpha2 0.065 spk bioB AFFX-r2-Ec-bioB-3_at spk bioC AFFX-r2-Ec-bioC-3_at spk bioD

Hello, I am looking for an explanation and/or fix for a discrepancy in the behaviour of the R lm.influence() function [ version R 1.5.0 (2002-04-29) ] and the same function in Splus [ Splus version 5.1 release 1, running on SGI IRIX 6.2]. The discrepancy is of concern because I am migrating some Splus scripts to R and need to ensure consistency of results. Specifically, when I fit a glm()

Hello all, I am trying to perform ANOVA on my sample data given below to see if any gene(column 1 stands for gene names) is differentially expressed after subjecting it to the 6 different experiments(columns 2 to 7 are experiments). Gene 14A_U133A_Detection 14B_U133A_Signal 88A_U133A_Signal 88B_U133A_Signal 183A_U133A_Signal 183B_U133A_Signal AFFX-BioB-5_at 403 409.3 611.5

I have a data frame which has the following data. data<-read.table("table.txt",header=TRUE) data X14A_U133A_StatPairs X14A_U133A_Detection X14B_U133A_Signal 1 AFFX-BioB-5_at 403.0 409.3 2 AFFX-BioB-M_at 757.3 574.4 3 AFFX-BioB-3_at 284.4 327.3 4 AFFX-BioC-5_at

Dear Help, After loading the pd.Citrus library and checking the DataFrame, I ran > the R code for: > > 1) 'oligo' > > > > {> library(pd.citrus) > Loading required package: RSQLite > Loading required package: DBI > > data(pmSequence) > > > show(pmSequence) > DataFrame with 341730 rows and 2 columns > fid sequence > <integer>

Hi, I have built R (current development version) and BioConductor 1.7 with portland group compiler on a AMD Opteron. When I ran qc assessment on Affymetrix latin square data set, I got the following output, Loading required package: affy Loading required package: Biobase Loading required package: tools Welcome to Bioconductor Vignettes contain introductory material. To view,

Hello all, I have a data file table.txt which i have attached. I am trying to pass the columns as arguments to a function "totnorm" where i am displaying a total normalization plot. The function is given below: totnorm<-function(x,y){scale<-sum(x)/sum(y);xlab<-colnames(x);ylab<-colnames(y);x1<-x[[1]];y1<-scale*y[[1]];plot(x1,y1,xlab=xlab,ylab=ylab,col=6, col.lab=4);}

Hello all, I have a data file table.txt which i have attached. I am trying to pass the columns as arguments to a function "totnorm" where i am displaying a total normalization plot. The function is given below: totnorm<-function(x,y){scale<-sum(x)/sum(y);xlab<-colnames(x);ylab<-colnames(y);x1<-x[[1]];y1<-scale*y[[1]];plot(x1,y1,xlab=xlab,ylab=ylab,col=6, col.lab=4);}

Dear Sir/Madam, I could succesfully normalise my microarray data using marrayNorm package. However, i have not been able to get normalised red and green channel intensities through R package. Is there a possibility to write a formula to calculate back the red and green channel intensities after normalisation of the data. Do I need to incorporate this formula in my R script? I am biologist

Hi-- While I agree that we cannot agree on the ideal algorithms, we should be taking practical steps to implement microarrays in the clinic. I think we can all agree that our algorithms have some degree of efficacy over and above conventional diagnostic techniques. If patients are dying from lack of diagnostic accuracy, I think we have to work hard to use this technology to help them, if we

hi all i started recently using R and i found myself stuck when i try to analyze microarray data. i use the "affy" package to obtain the intensities of the probes, i have two CTRs and two treated. HG.U133A.Experiment1.CEL HG.U133A.Experiment2.CEL HG.U133A_Control1.CEL HG.U133A_Control2.CEL 1007_s_at 2156.23115 467.75615 364.60615 362.11865

Hi everybody, I tried to analyze a custom Affymetrix 3'-biased Array. So I wanted to make a cdf package. (My CDF file size is 1.12Go). I tried several methods but the same error occured Method 1 > #Set the working directory > setwd("D:/Analyse R/Cel files") > #library to create cdf env > library("makecdfenv") >#Create cdf environment >pkgpath

I have CEL files from Affymetrix Mouse Array 430_2 and am trying to get the the individual PM intensities (11 per gene) for each sample. I would like to write out this into a tab delimited text file. Where am I stalling? This is what I've done: Change dir(to where CEL files are saved) Data <- ReadAffy() eset <- rma(Data) write.exprs(eset, file="mydata.txt") With this I am

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?

Dear All, Thank you kindly for such detailed replies. I was looking to overlay data using algorithms so that i am able to tell which genes are differentially expressed due to changes in copy number. I did a pubmed search and found only 7 literature pieces all of which use in-house algorithms. I am yet to explore Gviz since it wouldn't work on R 2.14, would try it after upgrading to R 2.15.

Hi, I use write.table() to write a file to an external xls file. the column names left-shift one position in output file. I check with col.names() row.names(), the file is fine. How to prevent the shifting? I71 I111 I304 I307 I305 I306 I114 I72 AFFX-BioB-5_at 6.66435 6.787807 5.335962 5.250163 6.47423 5.882104 5.965109 6.591687195 AFFX-BioB-M_at 6.163227 5.965427 4.665569 2.743531 6.097244

Hi all, What are current methods people use in R to identify mis-spelled column names when selecting columns from a data frame? Alice Johnson recently tackled this issue (see [BioC] posting below). Due to a mis-spelled column name ("FileName" instead of "Filename") which produced no warning, Alice spent a fair amount of time tracking down this bug. With my fumbling fingers

Dear List, My data consist of nine columns and about 50,000 rows. It looks like this. -9.0225 3.46464 2.80926 -0.3847 3.73735 1.1058 -2.98936 1.38901 -8.1846 -2.4315 -5.1189 1.8225 3.3798 1.7874 4.693 -3.9286 1.4266 5.7849 -3.4894 -4.0305 3.7879 3.5195 2.9186 2.8685 -6.126 4.978 4.9381 4.5282 3.62558 -3.0455 4.6518 1.39746 0.68652 3.5708 -3.6404 -4.2963 -1.3183 0.6752 -4.0382 -2.5386

I am very new to R. I was trying to load some publicly available Expression data in to R. I used the following commands mydata<-read.table("dataALLAMLtrain.txt", header=TRUE, sep ="\t",row.names=NULL) It reads data without any error Now if I use edit(mydata) It shows only 3916 entries, whereas the actual file contains 7129 entries) My data is something like Gene Description