similar to: How to a handle an error in a loop

This ought to work: resultdt <- lapply(PGWide[, 240:389], function(x, ...) try(tdt(x, ...))) You can then check the class of each component to see which one failed. Andy From: Farrel Buchinsky > > "Berton Gunter" <gunter.berton at gene.com> wrote in message > news:008601c67097$de1b46e0$5bc4fea9 at gne.windows.gene.com... > > ?try > > > > as in

I am using dgc.genetics to perform TDT analysis on SNP data from a cohort of trios. I now have a file with about 6008 variables. The first few variables related to the pedigree data such as the pedigree ID the person ID etc. Thereafter each variable is a specific locus or marker. The variables are named by a pattern such as "Genotype.nnnnn" with nnnnn corresponding to a number which

I am involved in a study where, as in most of life, men demonstrate themselves to be recalcitrant. So while we have many probands and most of their mothers we only have about 50% of the trios being complete. I have been running tdt and trio.types. It appears as if it is ignoring the duos. Sometimes a duo can be informative. For instance Father ..missing Mother 1/2 Proband 1/1 This duo shows that

Bottom Line Up Front: How does one reshape genetic data from long to wide? I currently have a lot of data. About 180 individuals (some probands/patients, some parents, rare siblings) and SNP data from 6000 loci on each. The standard formats seem to be something along the lines of Famid, pid, fatid, motid, affected, sex, locus1Allele1, locus1Allele2, locus2Allele1, locus2Allele2, etc In other

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

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.

Hi all, We are using two methods to identify SNPs. One is based on resequencing the genome and aligning the reads to the sequenced genome to identify SNPs (data available for 44 individuals). Another is based on SNP array with selected loci (30000 loci, 870 individuals). I want to compare the results from the resequencing based minor allele frequency and Array based minor allele frequency.

Hi Mr Tierney, I have noticed an error message from R 1.12.x's CMD check for a while (apparently prof Ripley completely rewrote CMD check in R 1.12+) e.g.: http://bioconductor.org/checkResults/2.7/bioc-LATEST/snpMatrix/lamb2-checksrc.html ---------------- * checking R code for possible problems ... NOTE Warning: non-unique value when setting 'row.names': ?new? Error in

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

How does one create a vector whose contents is the list of variables in a dataframe pertaining to a particular pattern? This is so simple but I cannot find a straightforward answer. I want to be able to pass the contents of that list to a "for" loop. So let us assume that one has a dataframe whose name is Data. And let us assume one had the height of a group of people measured at

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

Does anyone know if the sib TDT has been implemented in R 1. Spielman, R.S., and Ewens, W.J. (1998) A sibship test for linkage in the presence of association: the sib transmission/disequilibrium test. Am J Hum Genet 62, 450-458 -- Farrel Buchinsky, MD Pediatric Otolaryngologist Allegheny General Hospital Pittsburgh, PA

I?m tryng to use the SPDEP package in my research in the field of population genetics. My data set has the following format: - x and y : coordinates, - Z: allelic frequency in each loci (in a total of 8 locis) - this variable can assume the values 0 ; 0.5 or 1. The objective is to verify if there is a possible spatial autocorrelation structure of the allelic frequency in a population of

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

R-users, I'm seeking any suggestions on optimizing some code for speed. Here's the setup: the code below is part of a larger chunk that is calculating Fst values across loci and alleles. This chunk is designed to calculate the proportion ('p.a') of an allele ('a') at a locus in each population ('p') and the proportion of individuals heterozygous for that

Hello, I have been using Xen on a Debian Lenny server for quite some time. I decided to build a new Dom0 using identical hardware, but newest version of Xen from repositories with Debian Squeeze. I attempting to create a new DomU on the new host which is similar to an existing DomU running on the older Lenny host. The DomU is a three NIC firewall. Two of the NICs are virtualized. One NIC is a

Hi all, This is really a stats question as much as an R question. I'm trying to do a joint scaling test (JST - see below) on some very oddly-distributed data and was wondering if anyone can suggest a good way of dealing with model violations and/or using R to evaluate how sensitive the model is to violations of the normality assumption. Here's a quick explanation of the analysis, the

#Hello, #I have a question about obtaining results from a loop I have written. #Below is a sample of individual genotypes from a genetic question I am working on called "P.genotype.sample ". P.genotype.sample<-matrix(10,10,10) P.genotype.sample[,1]<-c(2,2,1,5,1,1,5,6,1,3) P.genotype.sample[,2]<-c(6,3,3,6,8,1,6,7,2,3) P.genotype.sample[,3]<-c(2,2,2,3,3,2,2,2,3,3)

I know that there are quite a few packages out that there for cluster analysis. The problem that I am facing is finding a package that will not incorporate all my samples into clusters but just the samples that fit a threshold (that I have not set yet and may need help finding the right level) for genotyping. It should be able to "no call" samples outside the clusters. It also needs to

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