similar to: creating a loop for multiple file

Hi, ? I am very new to R. So, pardon my dumb question. I was trying to write my own function to run a different model (perform an ordered logistic regression) using the example in website http://pngu.mgh.harvard.edu/~purcell/plink/rfunc.shtml But R returns a error `R Error in eval(expr, envir, enclos) : object 's' not found' when I run it. What am I doing wrong here? Here's

Hi all, I am running Stepwise logistic regression and i have : 1- Multiple covatiates included in each model (No missing data) 2- Genotype data (SNPs) about 500,000 . I partitioned the data to multiple files (there are missing data) I run the step by including all the covariates and one SNP at each model. but i got this message : number of rows in use has changed: remove missing values? In

Dear UseR, I get an error when I run "R CMD check" on my .tar.gz file package, and I don't understand why since I don't obtain any error with "R CMD check" on the package directory. Do you have any idea ? $ sudo ./R-2.11.0/bin/R CMD check eqtl_1.1.tar.gz and $ sudo ./R-2.11.0/bin/R CMD --check-subdirs=no eqtl_1.1.tar.gz return an Error * checking for working

Hello, When programming it is better to use dat[["variable"]] than dat$variable. So your code could be pfas.pheno[[cat.var]] <- NA pfas.pheno[[cat.var]][pfas.pheno[,i] <= quantile(pfas.pheno[,i],0.25, na.rm =T)] <- 0 etc. Untested. Hope this helps, Rui Barradas On 4/19/2018 7:20 PM, Ding, Yuan Chun wrote: > Hi All, > > I want to create a categorical variable,

> On Apr 19, 2018, at 11:20 AM, Ding, Yuan Chun <ycding at coh.org> wrote: > > Hi All, > > I want to create a categorical variable, cat.pfoa, in the file of pfas.pheno (a data frame) based on log2pfoa values. I can do it using the following code. > > pfas.pheno <-within(pfas.pheno, {cat.pfoa<-NA > cat.pfoa[pfas.pheno$log2pfoa

Hi All, I want to create a categorical variable, cat.pfoa, in the file of pfas.pheno (a data frame) based on log2pfoa values. I can do it using the following code. pfas.pheno <-within(pfas.pheno, {cat.pfoa<-NA cat.pfoa[pfas.pheno$log2pfoa <=quantile(pfas.pheno$log2pfoa,0.25, na.rm =T)]<-0 cat.pfoa[pfas.pheno$log2pfoa >=quantile(pfas.pheno$log2pfoa,0.75, na.rm =T)]<-2

> On Apr 19, 2018, at 1:22 PM, David Winsemius <dwinsemius at comcast.net> wrote: > > >> On Apr 19, 2018, at 11:20 AM, Ding, Yuan Chun <ycding at coh.org> wrote: >> >> Hi All, >> >> I want to create a categorical variable, cat.pfoa, in the file of pfas.pheno (a data frame) based on log2pfoa values. I can do it using the following code.

I am trying to find a convenient way to control line colors when printing from a for loop using the lines command. Right now I have solved this by creating a colors vector that is refered to in the loop with index. However, the colors choosen here are just 1,2,3,4,5... I would like to get colors from the col = rainbow(x) that you can use in plot() and set the to be my number of lines (I think

Dear List Members, I have encountered two problems when using the step function to select models. To better illustrate the problems, attached is an R image which includes the objects needed to run the code attached. lm.data.frame have factor variables with 3 levels. The following run shows the first problem. AICs (* and **) are different. I noticed that the Df for rs13482096:rs13483699 is 4,

Dear List Members, I have encountered two problems when using the step function to select models. To better illustrate the problems, an R image (step.add1.test.RData) which includes the objects needed to run the code (step.add1.test.R) can be found at www.biostat.wisc.edu/~pwang/r-help/<http://www.biostat.wisc.edu/%7Epwang/r-help/> lm.data.frame have factor variables with 3 levels. The

Dear R users, This command works (calling a programm -called whap- with file specifiers etc.): >system('cmd /c "c:\\pheno\\whap --file c:\\pheno\\smri --alt 1 --perm 500"', intern=TRUE) Now I need to call it from a loop to replace the "1" by different number, however I get lost using the quotes: I tried numerous versions of: >i<-1

Dear R users: I'm new to R and am trying to fit a mixed model Cox regression model with coxme function. I have one two-level factor (treat) and one covariate (covar) and 32 different groups (centers). I'd like to fit a random coefficients model, with treat and covar as fixed factors and a random intercept, random treat effect and random covar slope per center. I haver a couple of

Hi, The program below work very well. (snps = c('rs621782_G', 'rs8087639_G', 'rs8094221_T', 'rs7227515_A', 'rs537202_C')) Selec = todos[ , colnames(todos) %in% snps] head(Selec) But, I have a data set with 1.000 columns and I need extract 70 to use (like snps in command above). This 70 snps are in a file. So I create a file to extract them with

Dear all, I'm having a few problems trying to reshape a data frame. I tried with reshape{stats} and melt{reshape} but I was missing something. Any help is very welcome. Please find details below: ################################# # data in its original shape: indiv <- rep(c("A","B"),c(10,10)) level.1 <- rpois(20, lambda=3) covar.1 <- rlnorm(20, 3, 1) level.2

Hi, Using package gclus in R, I have created some graphs that show the trends within subgroups of data and correlations among 9 variables (v1-v9). Being interested for more details on these data I have produced also the var-covar matrices. Question: From a pair of two subsets of data (with 9 variables each, I have two var-covar matrices for each subgroup, that differ for a treatment on one

Dear R developers: I am a PHD candidate student in the school of public health of Peking University and my major is genetic epidemiology. I am learning the FAM-MDR algorithm, which is used to detect the gene-gene and gene-environment interactions in the data of pedigree. The codes were written by Tom Cattaert of the University of Liege. The algorithms and the sample datasets are available at

Hi I'm running QDA on some data and calculating the discriminant function. qda.res <- qda(type ~ npreg + glu + bp + skin + bmi + ped + age) ind_yes <- c(1:N)[type == "Yes"] > ind_no <- c(1:N)[type == "No"] > cov_yes <- cov(table[ind_yes, 1:7] ) > cov_no <- cov(table[ind_no, 1:7] ) > covar<-list(cov_no, cov_yes) qdf<- function(x,

>>>>>>>>>>>>>>><<<<<<<<<<<<<<<< Pheno-Mint upsmon # /sbin/upsdrvctl start Network UPS Tools - UPS driver controller 2.6.1 Network UPS Tools - Generic HID driver 0.35 (2.6.1) USB communication driver 0.31 This PowerCOM device (0d9f:0004) is not (or perhaps not yet) supported by usbhid-ups. Please make sure

I have a solution (actually a few) to this problem, but none are computationally efficient enough to be useful. I'm hoping someone can enlighten me to a better solution. I have data frame of chromosome/position pairs (along with other data for the location). For each pair I need to determine if it is with in a given data frame of ranges. I need to keep only the pairs that are within any of

Dear R-devel, I am writing for help on how I should include parallel sets of data in my package. Brief summary: I am new to using data within packages. I want a user to be able to specify one of two alternative versions of within-package datasets to use, and I want to load just that one. I have a solution that works, but it doesn't seem as simple as it should be from a user's