similar to: R, joint scaling test, quantitative genetic analysis & sensitivity to model violations

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

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

Dear R-experts, My problem is how to handle a 10GB data file containing genotype data. The file is in a particular format (Illumina final report) and needs to be altered and merged with phenotype data for further analysis. PERL seems to be an frequently used solution for this type of work, however I am inclined to think it should be doable with R. How do I open a text-file, line by line,

Hi R-help folks, I have been doing some single SNP association work using snpMatrix. This works well, but produces a lot of false positives, because of population structure in my data. I would like to correct the p-values (which snpMatrix gives me) for population structure, possibly using principle component analysis (PCA). My data is complicated, so here's a simple example of what

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

Hi, I want to analyse DNA sequence data (mtDNA) in R as in calculate Fst, Heterozygosity and such summary statistics. Package Adagenet converts the DNA sequence into retaining only retaining the polymorphic sites and then calcuates Fst.. but is there any other way to do this? I mean analyse the DNA sequence as it is.. and calculate the statistics? Thanks! [[alternative HTML version deleted]]

Hi, I am new to R. and even though I've made my code to run and do what it needs to . It is taking forever and I can't use it like this. I was wondering if you could help me find ways to fix the code to run faster. Here are my codes.. the data set is a bunch of 0s and 1s in a data.frame. What I am doing is this. I pick a column and make up a new column Y with values associated with that

I'm trying to put two plots side-by-side in two panels. Since the y-axis of the two plots is the same, I want to leave out the y-axis of the second plot. And the two plots look quite separate from each other. Is there any way to have them stay closer to each other? I've tried to adjust mar option of par but it has a global effect as I see the left margin of the first plot will be

Hi folks I have some tasks for you on the Xen packages: * copyright file I doubt that this is in any way current. * pvgrub This contains several parts which needs to be statically linked together: - minios, libxenctrl, libxenguest, libxenstore, all built out of the xen tree, - patched grub, - patched newlib and - a libz. - ioemu/dom0 userspace The upstream build uses a clone

On Wed, Jun 26, 2013 at 01:48:03PM -0400, Alexandre Rebert wrote: > We found a crash in qemu-dm contained in the xen-utils-4.1 package. You are being > contacted because your are listed as one of the maintainer of xen-utils-4.1. xen-utils-4.1 is not in unstable, so this is not really helpful. > The bug report that will be submitted to the bug tracker is available at the > following

Has something changed in R that requires an update in the genetics package by Gregory Warnes? I am using R version 2.5.0 This used to work > summary(founders[,59]) to prove that it is a genotype class > class(founders[,59]) [1] "genotype" "factor" Now when I issue the command: > summary(founders[,59]) I get: Error in attr(retval, "which") <- which :

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

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

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

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.

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

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

Hello, I am trying to simulate 10 relicates of 100-tables. Each table is a 2 x 3 and 80% pf the tables are true nulls and 20% are non-nulls. The nulls follow the Hardy Weinberg distribution (ratio) 1:2:1. I have the code below but the p-values are not what I am expecting. I want to use the Cochran Armitage trend test to get the p-values. num.reps=10 num.vars=1000 pi0 = 80 num.subjects = 100

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