similar to: Slow ttests in R-devel

Hi, I am relatively new to R and Bioconductor and am trying to filter the topTable that I generated of differentially expressed genes from my normlized eset file comprised of ~ 40 HG-133A Affy microarrays . I would like to see if particular probesets are represented in this list. Alternatively I would like to generate a topTable of differentially expressed genes using only specified probesets

Hi, I am a Ph.D. student from Québec, Canada. I’m a beginner with R and Bioconductor. Until now the only experience I have is in analyzing microarray data using affy and limma packages. Now I am trying to analyze Rat Gene 10 st arrays and I would like to run RMA analysis and Smyth moderated t test on those arrays. Since no cdf official package is available for those arrays, after reading many

I can use stepAIC on an lme object in 1.6.2, but I get the following error if I try to do the same in 1.7.0: Error in lme(fixed = resp ~ cov1 + cov2, data = a, random = structure(list( : unused argument(s) (formula ...) Does anybody know why? Here's an example: library(nlme) library(MASS) a <- data.frame( resp=rnorm(250), cov1=rnorm(250), cov2=rnorm(250),

First, here is your message as it appears on R-help. On 10/14/2012 05:00 AM, r-help-request@r-project.org wrote: > I?m trying to set up proportional hazard model that is stratified with > respect to covariate 1 and has an interaction between covariate 1 and > another variable, covariate 2. Both variables are categorical. In the > following, I try to illustrate the two problems that

Hello all! I have a problem that calls for a better understanding, than mine, of how lme() uses the random part of the call. The dataset consists of eleven field trials (Trial) with three replicates (Block) and four fertiliser treatments (Treat). Analysing for example yield with lme() is easy: m1 <- lme(Yield ~ Treat, data=data, random =~1| Trial/Block) giving estimates of

the study design of the data I have to analyse is simple. There is 1 control group (CTRL) and 2 different treatment groups (TREAT_1 and TREAT_2). The data also includes 2 covariates COV1 and COV2. I have been asked to check if there is a linear or quadratic treatment effect in the data. I created a dummy data set to explain my situation: df1 <- data.frame( Observation =

Dear R users, I am running a loop with the integrate function. I have pasted the code below. I am integrating a function from time=0 to the time value in every row. I have to perform this integration over thousands of rows with different parameters in each row. Could someone please suggest if there is an efficient/faster/easier way to do this by avoiding the loops ? Thank you so much for your

Hi all I do not understand why I am getting the following error message. Can anybody help me with this? Thanks in advance. install.packages("cmprsk") library(cmprsk) result1 <-crr(ftime, fstatus, cov1, failcode=1, cencode=0 ) one.pout1 = predict(result1,cov1,X=cbind(1,one.z1,one.z2)) predict.crr(result1,cov1,X=cbind(1,one.z1,one.z2)) Error: could not find function

Hello All, I need your help. I am analysing affymetrix data and have to select the probe-set that has median expression among all the probe-sets for same gene. This way I want to remove the redundancy by keeping the analysis to single gene entry level. I am fully aware that it is not a nice thing to do but I just have to do it. To do so, I came across 'findLargest' function of

I have a fairly large model: > length(Y) [1] 3051 > dim(covariates) [1] 3051 211 All of these 211 covariates need to be nested hierarchically within a grouping "class", of which there are 8. I have an accessory vector, " cov2class" that specifies the mapping between covariates and the 8 classes. Now, I understand I can break all this information up into individual

A package uses VignetteEngine: knitr; the package itself does not Suggests: knitr, but it Suggests: BiocStyle which in turn Suggests: knitr. Nonetheless, R CMD check fails indicating that a package required for checking is not declared. Is it really the intention that the original package duplicate Suggests: knitr? This is only with a recent R. In detail, with $ Rdev --version|head -3 R Under

We are trying to compile and run the ttest.c example that comes with R (in C:\Program Files\R\rw1081\src\library\windlgs\src\ttest.c). After compiling it with MS Visual C++ we load the DLL with dyn.load. So far it seems good, but when we try to call it from R (after running C:\Program Files\R\rw1081\src\library\windlgs\R\windlgs.R) R crashes. We have tried changing the exports from DLL but have

Hello to all !!! I have some issues with some users that login to the same account through imap from many devices like: mobile,desktop/tablet !!! Issues like: 1. When a new email is arrived is not appearing to all devices... 2. New email is arriving to some other devices after a long period of time ... Generally issues like that .... Does anyone have an idea of how to solve this ..?

Hello there Larry ! No it is not a client issue... Because i have tried many clients and all the same issue ! Actually the 1st client that refreshes the new email appear all others not ! I have tried RoundCube/Outlook/Thunderbird/Android Email... etc All have the same issue ..? -----Original Message----- From: Larry Rosenman [mailto:larryrtx at gmail.com] Sent: Tuesday, July 18, 2017 8:51 PM

Hello list, I have a similar issue as this post http://tolstoy.newcastle.edu.au/R/e6/help/09/04/11438.html#options2 and I used the suggestion provided by Jorge with modifications to my data do.call(c,lapply(your_list_with_the_t_tests,function(x) x$p.value)) but I am getting the following error after excuting the code B<-by(eo,eo$PlateID, function(.sub) t.test(mcp1~Self_T1D,data=.sub,

Hello, I would like to do a large number of e.g. 1000 paired ttest using the by-function. But instead of using only the data within the 1000 groups, R caclulates 1000 times the ttest for the full data set(The same happens with Wilcoxon test). However, the by-function works fine with the lme function. Did I just miss something or is it really not working? If not, is there any other possibility to

Hello there !! Yes I know .... Despite this it not shown at all ! -----Original Message----- From: Larry Rosenman [mailto:larryrtx at gmail.com] Sent: Tuesday, July 18, 2017 9:00 PM To: it at mrit.gr Cc: dovecot at dovecot.org Subject: Re: Dovecot imap Remember that the first client to READ the message will set \Recent, and the rest will show the mail as read. -- Larry Rosenman

Hello. Im hoping someone can help with a grouping question related to the "random=" statement within the nlme function. How do you specify that some grouping levels are inner to others? I tried several things, given below. Lets say I have a data frame with five variables, resp, cov1, ran1, ran2, group1, and group 2. The formula is resp~cov1 + ran1 + ran2, where the ran are random

Hello there ! Do you see anything wrong on the config i sent ? -----Original Message----- From: Aki Tuomi [mailto:aki.tuomi at dovecot.fi] Sent: Tuesday, July 18, 2017 9:20 PM To: nlekkas at gmail.com; Larry Rosenman Cc: dovecot at dovecot.org Subject: RE: Dovecot imap Can you provide doveconf -n please? Aki > On July 18, 2017 at 9:06 PM Nick Lekkas <nlekkas at gmail.com> wrote:

Hi, I discover that when I save a workspace containing a genefilter (pkg from Bioconductor) object I cannot open no more after. I have to restore the .RData file from a backup to be able to start R again. I didn't upgrade to Version 2.2 but I'm not sure that it will solve the problem. Did anyone have encounter the same problem? Below is a short r session to reproduce the error: ...