similar to: Could not find createData function

Hi, I am using "*Maanova* package" to do anova. I have created *datafile* with probeID as the first column, which is a tab limited text file and also created *designfile*. I have created *readma object* which is named as abf1. >From that readma object, i have to create data object by using *createData*function and also i hav to create model object by using *makemodel* function,

Hi, Am using maanova package for doing anova.But am getting error like this..plz, help me regarding this.. > TGR=read.madata("rmaexpr.dat",designfile="design.dat") Reading one color array. Otherwise change arrayType='twoColor' then read the data again Warning messages: 1: In read.madata("rmaexpr.dat", designfile = "design.dat") : Assume that

Hi, I am trying to run an analysis with the package maanova and I am not getting success. I suppose that I am wrong on set up the formula, so the issue may not be related to R, properly. I have two varieties of plants (V1 and V2). A group of each ones were treated and another was not treated. After treatment, in three different time RNA was collected from treated and from not treated plants for

I'm working with snow and created a local cluster. So far, the same code has always worked (please see below). However, now I receive a message that the connection with the nodes cannot be opened. I restarted my workstation but that didn't help. Is there a known solution for this problem? Thanks a lot for any help. bram foubert library(snow) cl =

When doing repeated regressions on large data sets, I'm finding that the time spent on garbage collection often exceeds the time spent on the regression itself. Consider this test program which I'm running on an Intel Haswell i7-4470 processor under Linux 3.13 using R 3.1.2 compiled with ICPC 14.1: nate at haswell:~$ cat > gc.R library(speedglm) createData <- function(n) {

Hello, Thanks everyone for helping me with the previous queries. step 1: Here is the orginal data: short sample ProbeID Sample_1_D Sample_1_C Sample_2_D Sample_2_C 1 224588_at 2.425509867 11.34031409 11.46868531 11.75741478 step 2: i calculate the variance of the sample using this R code x<-1:20000 y<-2:141 data.matrix<-data.matrix(data[,y])#create data.matrix

Hi, I am interested in using the cast function in R to perform some aggregation. I did once manage to get it working, but have now forgotten how I did this. So here is my dilemma. I have several thousands of probes (about 180,000) corresponding to each gene; what I'd like to do is obtain is a frequency count of the various occurrences of each probes for each gene. The data would look

Dear R-users: I am using the package MAANOVA to analyze microarray data and have encountered problems when trying to plot data. I have tried emailing a MAANOVA discussion group, as well as the author of the package, and have not yet received a response so I am hoping that someone on this listserv can be of assistance. There are several functions in MAANOVA (riplot, resiplot) which call the

Full_Name: Henrik Bengtsson Version: 1.5.1 OS: WinMe Submission from: (NULL) (217.210.0.243) In the Perl script $R_HOME/bin/check there is a bug under the section "Check R code for syntax errors" where the 'Rfiles <- c(...)' is build up. If there are too many files in @Rfiles the source code line generated will be too long and weird things will happen, e.g. strange

I'm trying to install packages on windows XP and I have trouble with command Rcmd build (R version 1.8.1) : In the Windows console for package maanova for example, answer is : C:\Documents and Settings\dillies\Mes documents\ghis\packages>Rcmd build maanova * checking for file 'maanova/DESCRIPTION' ... OK * preparing 'maanova': * cleaning src *

I have a file with a data in columnar format like below: probeID rc_AI104113_at rc_AI178259_f_at rc_AI179134_i_at rc_AI179134_f_at rc_AI104113_at rc_AA819429_f_at How can I rewrite it in the format below: 'rc_AI104113_at', 'rc_AI178259_f_at', 'rc_AI179134_i_at', 'rc_AI179134_f_at', 'rc_AI104113_at', 'rc_AA819429_f_at' Is there any function to do

Here is my R Code x<-1:20000 y<-2:141 data.matrix<-data.matrix(data[,y])#create data.matrix variableprobe<-apply(data.matrix[x,],1,var) variableprobe #output variance across probesets hist(variableprobe) #displaying histogram of variableprobe write.table(cbind(data[1], Variance=apply(data[,y],1,var)),file='c://variance.csv') #export as a .csv file. Output in Excel all in 1

I am trying to use lme to fit a mixed effects model to get the same results as when using the following SAS code: proc mixed; class refseqid probeid probeno end; model expression=end logpgc / ddfm=satterth; random probeno probeid / subject=refseqid type=cs; lsmeans end / diff cl; run; There are 3 genes (refseqid) which is the large grouping factor, with 2 probeids nested within each refseqid,

Hi Everyone, Thanks for all the help with the previous queries. Here is what i want to do. i have 20000 probesets-->calculate all the variance accross all the probesets-->filter out probesets that are low so now i ended up with only 10000. The 10000 is fine but when i export to excel, it is missing the probeID. Here are my code and examples. #########calculate the variance across the

Hi, I run a maanova analysis and found this message error: Error in ma.svd(X, 0, 0) : 0 extent dimensions I did a google search and found this: \item ma.svd: function to compute the sigular-value decomposition of a rectangular matrix by using LAPACK routines DEGSVD AND ZGESVD. \item fdr: function to calculate the adjusted P values for FDR control. I did a search for LAPACK and

Hi I'm using a function (arrayview from the maanova package) that produces 12 plots, all in separate windows. How can I get each one to print to a jpeg file as the plots are produced? Alternatively, is it possible to get dev.print (jpeg.....) to print all open graphics devices to separate windows? Thanks in advance, Nat Street -- Nathaniel Street University of Southampton

Hello, I am basically familiar with R and am trying to import a module that someone else has written. I know that it must go into the R library but even after I place the file there R doesn't recognize it. The module is maanova, available from the Churchill lab group for analysis of microarray data, if anyone is familiar with it. Any ideas/help? Thanks, Heather --

Dear R users, I am using the beadarray package. I am trying to upload raw bead-level data using these commands: ######################################################## library(beadarray) datadir <- ("C:/Computer_programs/R/beadarray/cecilia") targets = read.table("targets.txt", sep = "\t", header = TRUE, as.is = TRUE) BLData = readIllumina(arrayNames =NULL,

inputfille snpid indid genotype gvariable probeid gene geneexpression rs1040480 CHB_NA18524 C/T 2 GI_19743926-I PTPRT 5.850586 rs1040480 CHB_NA18526 C/C 1 GI_19743926-I PTPRT 6.028641 rs1040480 CHB_NA18529 C/C 3 GI_19743926-I PTPRT 5.944392 rs1040481 CHB_NA18532 C/C 1 GI_19743926-I PTPRT 5.938578 rs1040481 CHB_NA18537 C/C 2 GI_19743926-I PTPRT 5.874439 rs1040481 CHB_NA18540 C/C 3 GI_19743926-I

Hello, unfortunately I have I big problem I can't solve. I have to analyse if a gene is tissue specific. For example for the gene xyz I have following expression values: Heart Liver Brain 8.998497 10.013561 12.277407 9.743556 10.137574 11.033957 For every tissue I have two values from two different experiments. Now I want to test if Heart is significant higher