similar to: Accounting for within family correlation in genetic analysis

Hello all: A question from a new user. I have data on a geo-referenced curvilinear grid. This is a grid with 75 rows and 51 columns, is not aligned north-south, and the rows and columns are not straight. (And the coordinates are in meters.) I want to make image plots of this data, but where the grid is deformed according to the correct locations of the grid points, instead of coming out

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 useRs, I'm trying to simply fill in the area under a curve using RGL. Here' the set up: x <- c(0.75,75.75,150.75,225.75,300.75,375.75,450.75,525.75,600.75,675.75, 0.5,50.5,100.5,150.5,200.5,250.5,300.5,350.5,400.5,450.5, 0.25,25.25,50.25,75.25,100.25,125.25,150.25,175.25,200.25,225.25) y <- c(0.05,4.91,9.78,14.64,19.51,24.38,29.24,34.11,38.97,43.84,

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

I'm trying to use a contributed package (rmetasim) to generate simulated genetic datasets. My scripts work fine when I run them on a Sun workstation running Solaris 7 and when I run them on a ~4 year old laptop PC that I have. However, when I run them on my new laptop (Dell Latitude D410 purchased in August 2005), the simulation will run for a short (variable) period of time, then R

I realized that the script I included in my original post (see below) was written for an older version of rmetasim and will not work with the current version. The only change that need be made to get my script to run with the latest release of rmetasim is to change the command 'simulate.landscape()' to 'sim.landscape()'. My apologies to anyone who tried to use my script and

adventurous burgundian rook elkhart butterball concave chaplin dustbin trout plane pedestal cinquefoil ely indigene choir curvilinear scald zing bramble braid cobol composition tripartite bust torpedo transverse marvin crestfallen troika molybdate aflame righteous aden diffusive lenin wilcox downright pittsburgh inflammable smear cathy orinoco

The classifly package uses rggobi to visualise classification boundaries in high-dimensions. Given p-dimensional training data containing d groups (the design space), a classification algorithm (classifier) predicts which group new data belongs to. Generally the input to these algorithms is high dimensional, and the boundaries between groups will be high dimensional and perhaps curvilinear or

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

Hi, I'm trying to make a chromosomal map in R by using the locus. I have a list of genes and their locus, and I want to visualise that so you can see if there are multiple genes on a specific place on a chromosome. A example of what I more or less want is below: http://www.nabble.com/file/p21474206/untitled.JPG untitled.JPG The genes and locus are here:

My data looks like this: > data name G_hat_0_0 G_hat_1_0 G_hat_2_0 G_0 G_hat_0_1 G_hat_1_1 G_hat_2_1 G_1 1 rs0 0.488000 0.448625 0.063375 1 0.480875 0.454500 0.064625 1 2 rs1 0.002375 0.955375 0.042250 1 0.000000 0.062875 0.937125 2 3 rs2 0.050375 0.835875 0.113750 1 0.877250 0.115875 0.006875 0 4 rs3 0.000000 0.074750 0.925250 2 0.897750 0.102000

On Fri, 16 Jan 2009, r-help-request at r-project.org wrote: > Date: Thu, 15 Jan 2009 13:29:03 +0100 > From: Pablo G Goicoechea <pgoikoetxea at neiker.net> > Subject: Re: [R] How to create a chromosome location map by locus ID > To: Sake <tlep.nav.ekas at hccnet.nl> > Cc: r-help at r-project.org > Message-ID: <496F2C0F.3040304 at neiker.net> > Content-Type:

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

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

R 2.5 windows XP I am getting an error from glm() that I don't understand. Any help or suggestions would be appreciated. N.B. 1<=AAMTCAREJ<=327900 > summary(data$AAMTCAREJ) Min. 1st Qu. Median Mean 3rd Qu. Max. 1.0 404.3 1430.0 6567.0 5457.0 327900.0 > fitglm<-glm(AAMTCAREJ~sexcat+H_AGE+SmokeCat+InsuranceCat+MedicadeCat+ +

Hello, I have a data-frame in which one-column is a factor: > str(data); `data.frame': 194 obs. of 8 variables: $ Type : Factor w/ 3 levels "Nuclear-Rec..",..: 1 2 2 2 2 2 2 2 2 2 ... $ Locus : num 0.000571 0.004000 0.001429 0.004857 0.007429 ... And I'd like to make a boxplot of the data$Locus values, where each level of the factor gets its own

Hello, I am trying to do some simulation using the rmetasim package and I've run to this problem. --beginning of error msg-- Error in "[<-"(`*tmp*`, slice[l, ], slice[l, ], value = c(0.200000002980232, : number of items to replace is not a multiple of replacement length --end of error msg-- Here is the script I used. --script starts here-- ## load 'rmetasim'

>From: "john hickey" <jmwhickey@hotmail.com> >To: fries@fcav.unesp.br >Subject: R genetic parameters >Date: Tue, 20 Jun 2006 11:20:45 +0000 >X-OriginalArrivalTime: 20 Jun 2006 11:20:48.0892 (UTC) >FILETIME=[94F903C0:01C6945B] >X-Virus-Scanned: by amavisd-new at fcav.unesp.br > > >Luiz, > >How large a genetic analysis will you be able to do in R,

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