similar to: Vector searching and counting speed optimization

The "genetics" package for handling single-locus genetic data is now available on CRAN in both source and Windows binary formats. The purpose of this package is to make it easy to create and manipulate genetic information, and to facility use of this information in statistical models. The library includes classes and methods for creating, representing, and manipulating genotypes

The "genetics" package for handling single-locus genetic data is now available on CRAN in both source and Windows binary formats. The purpose of this package is to make it easy to create and manipulate genetic information, and to facility use of this information in statistical models. The library includes classes and methods for creating, representing, and manipulating genotypes

Hello All, Once again thanks for all of the help to date. I am climbing my R learning curve. I've got a few more questions that I hope I can get some guidance on though. I am not sure whether the etiquette is to break up multiple questions or not but I'll keep them together here for now as it may help put the questions in context despite the fact that the post may get a little long.

Hello R-help community, I have another question about filtering datasets. Please consider the following "toy" data matrix example, called "x" for simplicity. There are 20 different individuals ("ID"), with information about the alleles (A,T, G, C) at six different loci ("Locus1" - "Locus6") for each of these 20 individuals. At any single locus

Hallo all, I have the following glm model: f1 <- as.formula(paste("factor(y.fondi)~", "flgsess + segmeta2 + udm + zona.geo + ultimo.prod.", "+flg.a2 + flg.d.na2 + flg.v2 + flg.cc2", " +(flg.a1 + flg.d.na1 + flg.v1 + flg.cc1)^2", " + flg.a2:flg.d.na2 + flg.a2:flg.v2 +

Dear all I am trying to compare the performances of several methods using the AUC0.1 and not the whole AUC. (meaning I wanted to compare to AUC's whose x axis only goes to 0.1 not 1) I came to know about the Mcneil Hanley test from Bernardo Rangel Tura and I referred to the original paper for the calculation of "r" which is an argument of the function cROC. I can only find the

Dear all, I want to compute the average of the three blocks for each x-variable which is equal slide in the code below. How can I do that ? block x1 x2 x3 x4 x5 1 23 22 23 24 23 1 21 25 26 21 39 1 23 24 22 23 23 2 20 21 23 24 28 2 32 23 34 24 26 2 19

Dear all, I try to compare the performances of several parameters to diagnose lameness in dogs. I have several ROC curves from the same dataset. I plotted the ROC curves and calculated AUC with the ROCR package. I would like to compare the AUC. I used the following program I found on R-help archives : From: Bernardo Rangel Tura Date: Thu 16 Dec 2004 - 07:30:37 EST

I might be missing something but I thought that AUC was a measure for comparing ROC curves, so there is nothing else needed to "compare" them. The larger AUC is the higher correlation of 2 variables compared. No other measures or calculations are needed. Jarek Tuszynski -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On

Please help. I found the code in the archive. The author of this script says: "The first function (seROC) calculate the standard error of ROC curve, the second function (cROC) compare ROC curves." Can some one explain to me what are the na, nn and r parameters which are used as the input to the following two functions? Thanks much in advance. > From: Bernardo Rangel Tura >

I evaluated the Bayes factor in the k=2 allele case with a "triangular" prior under the null as in the example in the help file: HWETriangBF2(nvec=c(88,10,2)) [1] 0.4580336 When I swap the n11 entry and n22 entry of nvec, I received totally different Bayes factor: > > HWETriangBF2(nvec=c(2,10,88)) [1] 5.710153 > In my understanding, defining the genotype frequency as

Hi everyone, I have an issue with a data conversion. First, I tried it with the reshape-package, but since it's quite a while that I used it, I feel kind of rusty... I have a data.frame like this: id Sample.Name Marker Allele.1 Allele.2 sample_id species 1 01_primer01 Dalb01 165 179

Dear R-Core, after switching to 2.3.0, all my trusted do.call constructs that worked in 2.2 and earlier fail. I noted that changes were introduced to do.call, but I could not find out how these relate to my problem. The following example works in 2.2 and earlier, but fails because rownames are partially NA. I can correct this by manually adding row names, but it's a bit of work to check this

I am about one step away from heaven on earth. I think only one step! I am using dgc.genetics to run a TDT test on thousands of genetic loci. I have learnt (through the help of others on this mailing list) to send the complex output to useful data frames which in turn allow me to look at the big picture and screen the thousands of loci. Resultdt<-lapply(PGWide[,240:290], tdt) the above

Dear list, I came across the following error for three of my newly written Rd-files: non-ASCII input and no declared encoding I can't make sense of this. Below I copied in one of the three files. Can anybody please tell me what's wrong with it? Thank you, Christian \name{tetragonula} \alias{tetragonula} \alias{tetragonula.coord} \docType{data} % \non_function{} \title{Microsatellite

Hi all, [this is a bit hard to describe, so if my initial description is confusing, please try running my code below] #WHAT I'M TRYING TO DO I'd appreciate any help in trying to speed up some code. I've written a script that converts a matrix of integers (usually between 1-10,000 - these represent allele names) into two new matrices of normally distributed values (representing

Hello, I'm having some trouble figuring out the correct model specification for my data. The system consists of multiple populations of an organism, which have been genetically sampled for several years. The problem is this: A minority of individuals are found in more than one sample, either they have survived into the next sampling at the same location, or have migrated to another another

Hello, I am working with a matrix of multilocus genotypes for ~180 individual snail samples, with substantial missing data. I am trying to calculate the pairwise genetic distance between individuals using the stats package 'dist' function, using euclidean distance. I took a subset of this dataset (3 samples x 3 loci) to test how euclidean distance is calculated: 3x3 subset used

Hello, I need some help with the simulatedSNPs function from scrime package. I am trying to simulate some genotype of a case/control disease locus. The allele frequence are cases/controls Sample cases controls 2000 .5 .10 1500 .6 .40 In each of the row, i need to simulate 100 snp and calculate the pvalue ##############Download Scrime

I'm sorry everyone for the inconvenience of spamming the R-help... Here's the complete post: Hi everyone, > > Since it's quite a while that I used the reshape package, I now feel kind > of rusty. > > I have a data.frame like this: > > > > id Sample.Name Marker Allele.1 > Allele.2 sample_id species