search for: celltypes

...__________________________________________________________________________ Toy Example ____________ # Dummy cross-validation routine set.seed(7771) TotalN<-162 TestN<-80 TrainN<-TotalN-TestN # Make a dummy frame with 11 kinds of "CellType" labels and 17 normal variables DummyCellTypes<-floor(runif(TotalN,0,11)+1) DummyParams<-data.frame(CellType=DummyCellTypes, matrix(rnorm(TotalN*17),TotalN,17)) DummyParams$CellType<-factor(DummyParams$CellType) table(DummyParams$CellType) TrainFDAs<-list(100) TestConfusions<-list(100) TestErrs<-rep(-1,100) i<-1 z<-...

Hello R-help. I am trying to make a stacked barplot where the color of the sections of each bar depend on another variable. > myData[1:11,] score percent marker cellType Malignant 1 0 100.00000 ESR1 (ER) Bladder.M(5) TRUE 2 0 80.00000 PAX8 Bladder.M(5) TRUE 3 1 20.00000 PAX8 Bladder.M(5) TRUE 4 0 100.00000 ESR1 (ER) Brain.N(3) FALSE 5 0

Dear R-helpers I have a problem related to the use of NLME I think is simply a matter of getting the nlme coding correct, but i cannot get my brain around it I am analysing some 24 growth curves of some cells , and i wanted to say that there are significant differences between the curves in two parameters that describe the pattern of growth. these parameters are from a logistic (r & k)

Here is an example of how to do it. > library(survival) > vfit <- coxph(Surv(time, status) ~ celltype + trt, data=veteran) > userinput <- data.frame(celltype="smallcell", trt = 1) > usercurve <- survfit(vfit, newdata=userinput) #the entire predicted survival curve > user2 <- summary(usercurve, time= 2*365.25) # 2 year time point > user2$surv [1]

Hello all, I am a medical student and as a capstone for my summer research project I am going to create a simple online web "calculator" for users to input their relevant data, and a probability of relapse within 5 years will be computed and returned based on the Cox PH model I have developed. The issue I'm having is finding a definitive method/function to feed the user's

Hi, I am new to model selection by coefficient shrinkage method such as lasso. And I became particularly interested in variable selection in Cox regression by lasso. I became aware of the coxpath() in R package glmpath does lasso on Cox model. I have tried the sample script on the help page of coxpath(), but I have difficult time understanding the output. Therefore, I would greatly appreciate if

Hello R-help group, I have a question about merging lists. I have two lists: Genes list (hSgenes) name chr strand start end transStart transEnd symbol description feature ENSG00000223972 1 1 11874 14412 11874 14412 DEAD/H box polypeptide 11 like 1DEAD/H box polypeptide 11 like 3DEAD/H box polypeptide 11 like 9 ;;

Hi: I have made a lot of progress reading and manipulating large data files, thanks to the help of several of you. I am now stuck with writing the final file with the following error (see also the full transcript below): Error in as.matrix.data.frame(x) : length of dimnames[2] not equal to array extent I do not know what it means and could not find how to get around that in the manual nor

I would like to organize my data as follows: I have a table that contains various data, and the numbers represent a level of similarity between these data, eg RF00013 has 100% similarity with the data RF00014. I would leave my table as a heatmap where darker colors represent higher similarity, and the lighter colors represent less level of similarity. I'm using version 2.11 of R. these