search for: tumor

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 a "new" tumor showed up). We assume there are many different reasons for why a tumor would be measured in one cycle and...

...1-1200", "1201-1300", "1301-1400", "1401-1532", "201-300", "301-400", "401-500", "501-600", "601-700", "701-800", "801-900", "901-1000"), class = "factor"), MCM.Cell.vs.MCM.Tumor = c(6L, 7L, 12L, 9L, 13L, 7L, 11L, 4L, 8L, 11L, 11L, 12L, 4L, 15L, 28L ), Ttest.Tumor.vs.Ttest.Cell = c(4L, 2L, 7L, 9L, 8L, 10L, 4L, 7L, 8L, 7L, 5L, 7L, 4L, 5L, 9L), Ttest.Cell.vs.MCM.Cell = c(66L, 22L, 14L, 7L, 11L, 6L, 12L, 7L, 9L, 8L, 7L, 9L, 9L, 5L, 20L), Ttest.Tumor.vs.MCM.Tumor = c(31...

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, because the R script I wrote works fine when it is run from a regular terminal ....

...k to see if arguments are passed. > if(length(args)==0){ > stop("no args specified") > } > ## Then cycle through each element of the list and evaluate the expressions. > for(i in 1:length(args)){ > print(args[[i]]) > eval(parse(text=args[[i]])) > } > print(TUMOR) > print(GERMLINE) > print(CHR) qsub shell script test.sh: > #!/bin/bash > > #Note: the single quote '...' around the --args ... "..." "..." is important! > R CMD BATCH --no-save --no-restore '--args TUMOR="tumor.bam" GERMLINE="g...

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 tried with split and compare but its not working can any one suggest how can i compare these type of Strings thanks in advance [[alternative HTML version deleted]]

...ssion data analysis. The group supports a variety of research projects in target and drug discovery as well as biomarker development for AVEO's growing pipeline of novel anti-cancer drugs, AVEO's Translational Research program utilizes a novel platform combining proprietary, inducible tumor models and bioinformatics approaches to discover, validate and generate therapeutics against molecular targets in oncology. We have generated large populations of tumors that exhibit inter-tumor heterogeneity similar to that seen in human tumor populations. Each tumor has been characterized by mic...

...brevity. On July 11, 2017 5:25:20 PM PDT, Bogdan Tanasa <tanasa at gmail.com> wrote: >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, because the R script I wrote works >fine when it is r...

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 ~ dose, data = lungtumor, teststat = "quad") > ca.test Asymptotic General Independence Test dat...

...t 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) > cox1a<-cph(surv.obj~factor(ecog)+factor(grade)+factor(tumor)+factor(extra),x=T,y=T) > coef1a<-coef(cox1a) > coef1a ecog=1 ecog=2 grade=2 grade=3 tumor=2 tumor=3 extra=1 0.3578954 0.8993140 0.4834090 0.5716166 0.7600330 1.5974558 0.8112942 > validate(cox1a,dxy=T,method="b",B=10)...

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! Sincerely, Alex [[alternative HTML ve...

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 = "Cellline/xenograft",tumor="primary,secondary,cellline",time = "0hr,1hr,2hr,4hr", id = "1,2,3,4,5,6,7,8,9") # Initialize exprSet object pD <- new("phenoData", pData=pd, varLabels=pd...

...or: package 'modeltools' required by 'coin' could not be found In addition: Warning messages: 1: package 'coin' was built under R version 2.6.0 2: package 'survival' was built under R version 2.5.1 3: package 'mvtnorm' was built under R version 2.5.1 > 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)))) > table(lungtumor$dose, lungtumor$tumor) 0 1 0 38 2 1 43 7 2 33 15 > independence_test(tumor ~ dose, data = lungtumor, teststat = &q...

...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 data generation (6 also). I paste the code I am using: library(MASS) Tumor <- c(rep("MM",20),rep("GBM",18),rep("LGG",17)) data.lda <- lda(data,Tumor) data.ld <- predict(data.lda) data.ldd <- data.frame(data.ld$x,data.ld$class) library(rggobi) data.g <- ggobi(data.ldd) library(classifly) generate_classification_data(data.lda,d...

...a) > fung.lor <- loddsratio(Fungicide) > fung.lor log odds ratios for group and outcome by sex, strain strain sex 1 2 M -1.596015 -0.8266786 F -1.386294 -0.6317782 > > fung.lor.df <- as.data.frame(fung.lor) > fung.lor.df group outcome sex strain LOR ASE 1 Control:Treated Tumor:NoTumor M 1 -1.5960149 0.7394909 2 Control:Treated Tumor:NoTumor F 1 -1.3862944 0.9574271 3 Control:Treated Tumor:NoTumor M 2 -0.8266786 0.6587325 4 Control:Treated Tumor:NoTumor F 2 -0.6317782 1.1905545 > Now, I want to test whether the odds ratios differ by sex or strain, so I do a weighted...

...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 data set. >library(survival) >data(rats) > str(rats) 'data.frame': 150 obs. of 4 variables: $ time : int 101 104 104 77 89 88 104 96 82 70 ... $ tumor : int 0 0 0 0 0 1 1 1 0 1 ... $ trt : int 1 1 1 1 1 1 1 1 1 1 ... $ litter: int 1 2 3 4 5 6 7 8 9 10 ... >m1<- coxme(Surv(rats$time, rats$tumor) ~ rats$trt + (1|rats$litter)) >m1 Cox mixed-effects model fit by maximum likelihood Data: rats events, n = 40, 150 Iterations= 10...

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)), rep(c(0, 1), c(33, 15)))) table(lungtumor$dose, lungtumor$tumor) ### Cochran-Armitage test (...

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 variables and tumor type (1 or 0) as dependent variable. 2 Fit in a 10 variable logistic model and calculate it...

...m 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 N2 N3 N4 T1 T2 T3 T4 I can do something like the following: if x object is my data matrix boxplot(x ~ c(rep('N',n),rep('T',n)), ylim=ylim, main=title) since the data is arranged as N1 T1, I don...

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...

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 hav...