similar to: Having some Trouble Data Structures

Hi, First my apologies for a non-working piece of code in a previous submission, I have corrected this error. I'm doing is individual based modelling of a pathogen and it's host. The way I've thought of doing this is with two dataframes, one of the pathogen and it's genes and effector genes, and one of the host and it's resistance genes. During the simulation, these things

Hi, I have some values in a list format generated by the following: Path_Number <- 0010 ID.Path <- formatC(0001:Path_Number, width=4, flag=0) # Make vector of ID's. No_of_Effectors <- sample(1:550, length(ID.Path), replace=TRUE) # Define Number of Effectors each individual gets. Effectors <- split(sample(1:10000, sum(No_of_Effectors), replace=TRUE), rep(ID.Path, No_of_Effectors))

Hi, I have the following data: Path_Number <- 5 ID.Path <- c(1:Path_Number) # Make vector of ID's. No_of_X <- sample(50:550, length(ID.Path), replace=TRUE) # X <- split(sample(1:10000, sum(No_of_X), replace=TRUE), rep(ID.Path, No_of_X)) Y <- lapply(X,function(x) sample(x, round(runif(1, min=10, max=50)))) X and Y are both lists, and I've made the following function to

Hi all, I'd like to write a piece of code which will remove columns from a matrix, if the column contains only one value, say every value in the column is a "3": Matrix <- matrix(NA, nrow=5, ncol=4) Matrix[,1] <- c(1,2,3,4,5) Matrix[,2] <- c(3,3,3,3,3) Matrix[,3] <- c(5,4,3,2,1) Matrix[,4] <- c(5,1,4,3,2) [,1] [,2] [,3] [,4] [1,] 1 3 5 5 [2,] 2

Dear all, I''m trying to write a function, that will take as an argument, some aligned genome sequences, and using a sliding window, do pairwise comparisons of sequence similarity. Coding the sliding window I think I can manage but what I''m trying to get to grips with is getting it so as every pairwise comparison is made, no matter how many genomes are added, from 3 to N. So if

Hi, This is probably a small query but one I'm struggling with: I have a list in which I had elements which were NA, I removed them, by doing: list2 <- lapply(list, na.omit), However this leaves the element there with 'character(0)' in place as well as attributes: e.g. [[978]] character(0) attr(,"na.action") [1] 1 attr(,"class") [1] "omit" I want

Dear list! I have run into a problem that seems very simple but I can't find any solution to it (have searched the internet, help-files and "An introduction to R" etc without any luck). The problem is the following: I would like to create a data.frame with two components (columns), the first component being a matrix and the second component a vector. Whatever I have tried so far, I

Dear R users & Experts, This is just a curiousity, I was wondering why the dominant eigenvetor and eigenvalue of the following matrix is given as the third. I guess this could complicate automatic selection procedures. 0 0 0 0 0 5 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 Please

Dear all, I would like to know if it is possible to fit in R a Cox ph model with time-dependent covariates and to account for hierarchical effects at the same time. Additionally, I'd like also to know if it would be possible to perform any feature selection on this model fit. I have a data set that is composed by multiple marker measurements (and hundreds of covariates) at different time

Hello, I would like to know if there is a function in R that will test for normality and handle censored data sets. Currently, I evaluate each censored data set by the extent to which a normal scores plot approximate a straight line. For complete data sets I use shapiro.test(). Below is an example of a censored data set. data1<-c(0.00, 0.00, 0.00, 5.86, 5.17, 8.17, 5.12, 4.92, 7.08,

Hi all, I have a list of genes present in 500 individuals, the individuals are the elements: Genes <- lapply(1:nrow(inds),function(x) sample(1:10000,inds$No_of_Genes,replace=TRUE)) (This was later written to a dataframe as well as kept as the list object: inds2 <- data.frame(inds,Genes=I(Genes))) I also have a vector of how many of those genes are expressed in the individuals, this can

Hi The cor function in the stats package calculates the correlation between columns of data, does anyone know if it is at all possible to calculate the correlation between rows instead ? Or is there an appropriate package or function that is more appropriate I'd like to calculate spearman & pearson correlations between rows. Many thanks Jason -- --------------------------------

Hi all, I realised that my last email question and code was probably going to be a bit of an eyesore for some people and that perhaps the best thing for me to do is to pose the question of what it is I want to achieve, rather than what I''ve written, if it helps people: I''m writing a simulation, and during that simulation I have a list of matrices – of variable number of

Hi all, I've written a function for a simulation which will - in general operation without being specific to the simulation scenario, duplicate or delete columns from a matrix based on two values which determine how many as a proportion of the matrix: the two values are always between 0.01 and 0.99: Dup.Dels <- function(matrix, values){ p.dup <-

Dear All, Apologies for sending this email to both list, but at this point I'm not sure which one could help me the most. I have 4 sets of data, 1 test and 3 different sets of controls. The measurements are binary, with a matrix of 0 and 1 I'm measuring across time (rows, ~815) the behaviour of organelles in the cell by microscopy in response to different stimuli (several measurements

I use the step() function occasionally, and I think I understand its objective, proper use, and limitations. Now I see stepwise model selection being used in what seems to be an unusual way, and I wonder if it is right or wrong. May I describe? Genetic mapping tries to find where in an animal's genome are genetic elements that influence a particular physical trait. Say there are 100

Hi All, Can anyone suggest how to make rsync work in order to replicate double-byte characters ? Thanks to anyone who can help aslay

Hi, I would like some extra information on the 'cgh' package in R. I noticed that there isn't much activity regarding this package on the R and BioC mailing list (I googled it). I started using this package and I have few questions: 1/ As I have a custom tiling like array @8um features resolution (affy), I have a lot of probes to work with. I'm assuming it is correct to

Dear R users, I am sorry to disturb you! But I really need your help for the usage of sigPathwy. Actually, I want a sliding window analysis for possible chromosome expression pattern mining. My research microorganism is a plant pathogen, Gibberella zeae, and I first used SAS to divide locus number with 10, 20, 30, or 40 on the fungal chromosome according to their location. I really

Dear list, I am needing to extract the estimate of overdispersion (deviance / residual degrees of freedom or c-hat) from multiple model objects - so they can then be used to compare the extent of overdispersion among alternative models as well as calculate qausi-AIC values. I have been unable to do this, despite consulting a number of manuals and searching the R-help. I am imaging that in