search for: tumoral

Hello, I didn't give enough information when I sent an query before, so I'm trying again with a more detailed explanation: In this data set, each patient has a different number of measured variables (they represent tumors, so some people had 2 tumors, some had 5, etc). The problem I have is that often in later cycles for a patient, tumors that were originally measured are now missing (or

Hi, I am trying to plot the following data so that it can be visually represented well. I tried the dotchart but I felt it was too spread out. Then I tried the barplot which is good enough for me. Is there a way to give the labels for the y-axis as in the dot chart? Also, I feel the grey level is confusing, so is there options for designs within the bars? I cannot use color as the journal wants

Dear all, please could you advise me on the following : I've written a R script that reads 3 arguments from the command line, i.e. : " args <- commandArgs(TRUE) TUMOR <- args[1] GERMLINE <- args[2] CHR <- args[3] ". when I submit the R script to a PBS HPC scheduler, I do the following (below), but ... I am getting an error message. (I am not posting the error message,

Hi, The problem is most likely, you need to call a R CMD BATCH with your arguments and the R-script inside of a shell script that you submit to your qsub. Unfortunately we don't use qsub anymore so can't test it, but it should be as follows: R-script eg. test.R: > ##First read in the arguments listed at the command line > args=(commandArgs(TRUE)) > > ##args is now a list of

Hi all, I got one problem with comparing strings like if any string is like "*RIGHT, EPICARDIUM: FOCUS, GRAY-WHITE, SINGLE, APPROX 0.6 CM IN DIAMETER*." and i have to compare "*GRAY-WHITE*" with the above string or otherwise i have to compare " *TUMOR BENIGN*" this string with "*MEDULLRY TUMOR BENIGN,TYP PHEOCHROMOCYTOMA*" i

BioInformatics Scientist Job Code: 10-TR25 Location: Cambridge, MA Description We are seeking a highly motivated, independent bioinformatics scientist to join a group of scientists, analysts and programmers to develop tools and methodologies for large-scale gene expression data analysis. The group supports a variety of research projects in target and drug discovery as well as biomarker

This sounds like an operating system specific question, in that "submit the R script to a PBS HPC scheduler" would be the kind of action that would run R with very different environment variables and possibly different access credentials than your usual interactive terminal. A thorough reading of the "Installation and Administration Guide" and some study of your HPC

Hello, Would you tell my how to extract a result from a test - it's justified because I need to run this test many times. Here is an example from authors' test: > library("coin") > lungtumor <- data.frame(dose = rep(c(0, 1, 2), c(40, 50, 48)), tumor = c(rep(c(0, 1), c(38, 2)), rep(c(0, 1), c(43, 7)), rep(c(0, 1), c(33, 15)))) > ca.test<-independence_test(tumor ~

Dear R help, I am having a problem with the Design package and my problem is detailed here. I fit a cox model to my data and validate the Somer's Dxy using the Design package. (Because of computation time problem, i only try 10 bootstrap samples for the time being) This is the model without stratification: > library(Design) >

Dear list, I need to read a big txt file (around 130Mb; 23800 rows and 49 columns) for downstream clustering analysis. I first used "Tumor <- read.table("Tumor.txt",header = TRUE,sep = "\t")" but it took a long time and failed. However, it had no problem if I just put data of 3 columns. Is there any way which can load this big file? Thanks for any suggestions!

Hi, I am having troubles with creating an eSet and would appreciate any help on the following problem. I am trying to create an eSet using the following code pd <- read.table(file="pdata.txt",header =TRUE,row.names=1); colnames(pd) <- c("type","tumor","time","id"); pdN <- list(type =

Dear sir, I am Shibu John from Thrombosis Research Institute India. It is a multidisciplinary organisation concerned with the interrelated problems of thrombosis and atherosclerosis. I was searching for Cochran armitage trend test program in R. Then I had seen your R coding for C-A trend test. I tried that in the R software. But I can?t run the program due the [Error: could not find function

Hello, I am trying to explore a classification with GGobi. I am trying to generate additional data according to the model so I can draw the decision boundaries on the GGobi plot. The problem is that I always get the same error: Error in predict.lda(model,data): wrong number of variables, even if I know that I used the same number of variables for the model generation (6) and for the additional

In the vcdExtra package on R-Forge, I have functions and generic methods for calculating log odds ratios for R x C x strata tables. I'd like to define methods for fitting weighted lm()s to the resulting loddsratio objects, but I'm having problems figuring out how to do this generally. # install.packages("vcdExtra", repos="http://R-Forge.R-Project.org")

Hi, I am new to R and AIC scores but what I get from coxme seems wrong. The AIC score increases as p-values decrease. Since lower AIC scores mean better models and lower p-values mean stronger effects or differences then shouldn't they change in the same direction? I found this happens with the data set rats as well as my own data. Below is the output for two models constructed with the rats

Dear R-enthusiasts, I am trying to do a Cochran-Armitage test for trend in R. After consulting google I found Torsten Hothorn's remark that the 'coin' library could be used. lungtumor <- data.frame(dose = rep(c(0, 1, 2), c(40, 50, 48)), tumor = c(rep(c(0, 1), c(38, 2)), rep(c(0, 1), c(43, 7)),

Hi, all, Anyone has experience on Logistf package? I am using logistftest in Logistf package to selelct diagnosis genes. The result seems not the same as I expected. I have 10 gene expression data for 27 tumor 1 and 11 tumor 0. I want to select the best one using Maximum likelihood ratio test in logistic regression model. This is the way my code works: 1. Read in 10 genes as independent

Hi: I am looking for some help in making two boxplots next to each other. I have a data like this: N1 T1 N2 T2 N3 T3 N4 T4 ... Nn Tn 7 8.2 4 5 8 10 4 5 ..... 10 11 I want to have box plot for all Normal samples (N1,N2,N3,N4,,,,Nn) and another box plot for all tumors (T1,T2,T3,T4,...Tn). I have data in a numeric class. If data is represented as N1

I am interested in plotting histograms for the following data Isoform Tumor_65_198 Tumor_50_192 Tumor_80_167 Tumor_80_204 Tumor_95_197 Tumor_70_189 Tumor_90_202 Tumor_40_177 Tumor_60_21 Tumor_70_174 Tumor_70_147 Tumor_50_5 ABCC4-2007 1 1 1 6 1 9 10 1 2 0 10 1 ABCC4-2008 5 8 7 5 3 10 5 5 7 3 10 3 ABCC4-2009 0 0 0 0 0 0 0 0 0 0 0 0 ABCC4-2010

Hello R users, I am trying to run a cox model for the prediction of relapse of 80 cancer tumors, taking into account the expression of 17000 genes. The data are large and I retrieve an error: "Cannot allocate vector of 2.4 Mb". I increase the memory.limit to 4000 (which is the largest supported by my computer) but I still retrieve the error because of other big variables that I have in