similar to: How to a handle an error in a loop [Broadcast]

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

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

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

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

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

Dear All, The following code extracts from NCBI very nice output for ONE allele of a SNP (often the allele with the second largest frequency - usually termed the minor allele). It gives an average minor allele frequency from all NCBI sources (which is what I want, except I'd like the addition of data for all the other alleles of one SNP) plus a table of minor allele frequencies from each

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

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

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.

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

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

Dear R listers, I have a data file looks like the following: Testing marker: s_1 --------------------------------------------- Allele df(0) -LnLk(0) df(T) -LnLk(T) ChiSq p 3 7995 29320.30 7994 29311.85 16.90 4e-05 (2229/8000 probands) Testing marker: s_2 --------------------------------------------- Allele df(0)

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

Last Friday, Gregory Chaitin (http://www.umcs.maine.edu/~chaitin/lm.html) mentioned that there can be no proof that a given code is the shortest for a problem, even within a language. Still, the script below, a replacement of the "TDT", one of the most frequently used tests in genetics (http://mustat.rockefeller.edu under "downloads") may get close. It contains a few

I have been merrily using the genetics package and more specifically have been using the makeGenotypes and genotypes function. I check my accomplishments by going > class(g2) [1] "genotype" "factor" and likewise > class(g1) [1] "genotype" "factor" Yet when I execute a command such as allele count I get this > allele.count(g1) D I [1,]

Hello, In a case control study how to calculate the risk allele or score allele. Regards GRR [[alternative HTML version deleted]]

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