search for: genotypized

#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)

#Hello, #I have would like to paste a single column of a matrix # in pair wise fashion with other columns based upon # even and odd column numbers. # I can do it in a very clunky fashion and I know there # must be a better way. below is a sample matrix and my extremely # clunky code that gets the job done for a small matrix, but i plan to # do this on a much grander scale. any help would be very

Hi. I was wondering if anyone might have some suggestions about how I can overcome a problem of "iteration limit reached without convergence" when fitting a mixed effects model. In this study: Outcome is a measure of heart action Age is continuous (in weeks) Gender is Male or Female (0 or 1) Genotype is Wild type or knockout (0 or 1) Animal is the Animal ID as a factor

Hello, My R skills are somewhere between novice and intermediary, and I am hoping that some of you very helpful forum members, whom I've seen work your magic on other peoples' problems/questions, can help me here. I have a matrix with the following format: (i) individual plants comprising many different genotype groups (i.e., a plant is genotype 1 or genotype 2 or genotype 3, etc). The

Hi, I am conducting an association analysis of genotype and a phenotype such as cholesterol level as an outcome and the genotype as a regressor using multiple linear regression. There are 3 possibilities for the genotype AA, AG, GG. There are 5 people with the AA genotype, 100 with the AG genotype and 900 with the GG genotype. I coded GG genotype as 1, AG as 2 and AA as 3 and the p-value for the

Hi, Could someone tell me if this is the correct model syntax for the following dataset: lme(height~treatment+genotype+treatment*genotype,drought,random=~genotyp e) The dataset has two factors: one fixed - treatment, and one random - genotype. I need to test the effect of both factors to identify their significance. There are multiple (but not equal) replicates at each level of genotype (the

Dear R users, I have a problem with something called "NaNs" in a nested mixed model. The background is that I have studied the number of insect nymphs emerging from replicated Willow genotypes in the field. I have 15 replicates each of 4 Willow genotypes belonging two 2 Willow species. Now I want to elucidate the effect of Willow genotype on the number of emerging nymphs. Previously I

Dear all, Lattice provides automatic coloring for subgroups on each panel by the simple use of a groups statement. For an application I want to change these colors to a predifined set. This works well using a panel function in stead of the default as long as there are only points in the graphs. When I set type="b" things get messed up. Any idea why? I include sample code for

Thanks Bert for all the help. I got the legend figured out Friday but left early becoz of long weekend so didn't get a chance to reply.. I modified the plot margins a little bit and Here's what I finally had... par(mar=c(c(10, 6, 6, 10) + 0.1)); par(xpd=FALSE); with (dataFrame, stripchart(marbles_buried ~ genotype, method="jitter", vertical=TRUE, col = c('blue',

-----Original Message----- From: Ghosh, Sandeep Sent: Thursday, June 30, 2005 5:43 PM To: 'Berton Gunter' Subject: plot legend outside the grid Thanks for the pointers... I managed to get everything to look and feel the way I want except for the legend to plot outside the grid... Thanks for the note on the par, but I'm not able to it to plot outside the plot grid.. dataFrame <-

I want to specify a two-factor model in lme, which should be easy? Here's what I have: factor 1 - treatment FIXED (two levels) factor 2 - genotype RANDOM (160 genotypes in total) I need a model that tells me whether the treatment, genotype and interaction terms are significant. I have been reading 'Mixed effects models in S' but in all examples the random factor is not in the main

Hello R Users, I am investigating the basic use of the LME function, using the following example; Response is Weight, covariate is Age, random factor is Genotype model.lme <- lme (Weight~Age, random=~ 1|Genotype) After summary(model.lme), I find that the estimate of Age is 0.098 with p=0.758. I am comparing the above model with the AOV function; model.aov <- aov (Weight~Age + Genotype)

Hi All, I've been working on updating the 'genetics' package. As a consequence of the upgrade, .First.lib() looks like: .First.lib <- function(libname, pkgname) { if (!require(combinat)) warning("Unable to load 'combinat' library. Function `diseq.ci' will fail.") require(gregmisc) genotype <-

Hi, I am trying to test for pairwise associations between genotypes ( Rows=individuals, Columns =genes, data are up to 4 genotypes per gene, some with 2,3 or 4) where each chisquare comparison is different depending on the genes tested. The test is the observed multilocus (across columns for each individual) genotypes vs the expectation, which is the product of the individual frequency for each

Hi All, I have a problem trying to get a set of columns recognised as a list and can't work out how to do it despite trawling through the mailing list archives, and docs. A short example... to.convert <- NULL n <- 6 for(x in 1:n){ to.convert <- paste(to.convert, paste((2 * x) -1, (2 * x), sep=":"), sep=",") } to.convert <- gsub("^,", "",

Hello all, thanks for your time and help. Below are my commands, and it generates a really nice plot, however I am not happy with the reorder() function. I would like the order to be the same as they appear in the genotype variable "genotype <- c("CJ1450 NW 4/25/12","CJ1450 BAL 4/25/12","CJ1450 NW 4/27/12","CJ1450 BAL 4/27/12","CJ1721 NW

I'm new to R (previously used SAS primarily) and I have a genetics data frame consisting of genotypes for each of 300+ subjects (ID1, ID2, ID3, ...) at 3000+ genetic locations (SNP1, SNP2, SNP3...). A small subset of the data is shown below: SNP_ID SNP1 SNP2 SNP3 SNP4 Maj_Allele C G C A Min_Allele T A T G ID1 CC GG CT AA ID2 CC GG CC AA ID3 CC GG nc AA

> From: kjetil halvorsen [mailto:kjetilh at umsanet.edu.bo] > > Martin Hoyle wrote: > > > > Dear Greg, > > Thanks for the new release. The decomposition of the SSQ is > just what I need! > > > I thought decomposition of the SSQ can be obtained with the split= > argument to summary.aov? That argument seems tro be new --- it didnt > exist two years

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,]

Sequenom has an odd format of calling a SNP genotype gg [1] "C" "GA" "A" "C" "C" "AG" "C" "C" "T" "G" homozygous A is called A and heterozygous is called AT The genetics package cannot handle the fact that some genotypes are declared with 2 letter while other are declared with only 1.