search for: alleles

...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 source (which would also be nice - but not necessary). Does there exist a package in R with coding which could extract the data from NCBI for all the alleles of one SNP ? I've looked at getBM() from package biomaRt and searched via...

Hi people, I have made some progress trying to work out how to solve this problem but I have got a bit stuck - sorry if this turns out to be a simple exercise . . Allelic Differentiation (AD) in genetics measures the number of different alleles between (say) two populations eg: Organisms in Pop 1 have alleles: a, b, c, d, e Organisms in Pop 2 have alleles: b, b, c, d, e Different (unique) alleles (n) are: a [unique() does not do what I want here for comparing these two vectors and I can't get combinations of unique() and duplica...

#Hello, #I have three data frames, X,Y and Z with two columns each and different numbers of rows. # creation of data frame X X.alleles <- c(1,5,6,7,8) X.Freq <- c(0.35, 0.15, 0.05 , 0.10, 0.35) Loc1 <- cbind( X.alleles,X.Freq) X <- data.frame(Loc1) #creation of data frame Y Y.alleles <- c(1,4,6,8) Y.Freq <- c(0.35, 0.35, 0.10, 0.20 ) Loc2 <- cbind(Y.alleles, Y.F...

...using sapply), I would be forever indebted. ##MY CODE library("MASS") ##run this example to see what I'm talking about above make.effects <- function(x,mn=0,var=1,cov=.5){ set.seed(x) return(mvrnorm(1,mu=c(mn,mn),Sigma=matrix(c(var,cov,cov,var),nrow=2),empirical=FALSE))} (alleles <- matrix(c(5400,3309,2080,1080,2080,1111,389,9362,6372,3787,2798,1009),ncol=4)) a12 <- array(sapply(alleles,make.effects),dim=c(2,nrow(alleles),ncol(alleles))) (a1 <- a12[1,,]) (a2 <- a12[2,,]) #I've set the population correlation = .5; empirical corr=.4635 cor(as.vector(a1),as.v...

I have a vector: alleles.present<-c("D3", "D16", ... ) The alleles present changes given the case I'm dealing with - i.e. either all of the alleles I use for my calculations are present, or some of them. Depending on what alleles are present, I need to make matrices and do calculations on those...

...e 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. Question 1: My first goal is to calculate the proportion of shared 1) behaviours and 2) alleles between numerous individuals. Pasted below ('propshared' function) is what I have now and and works very well for calculating the proportion of shared behaviours where the data is formatted with each column as a behaviour and each row an individual. Microsatellite genotypes are formatted...

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 (e.g., "Locus1" or "Locus2", ... or "Locus6"), the individuals have either one allele (from the set of A,T,C,G) or one other allele (from...

...ng genotypes (unordered allele pairs) and haplotypes (ordered allele pairs). Genotypes and haplotypes can be annotated with chromosome, locus, gene, and marker information. Utility functions compute genotype and allele frequencies, flag homozygotes or heterozygotes, flag allele carriers of certain alleles, count the number of a specific allele carried by an individual, extract one or both alleles, estimate and generate confidence intervals for measures of single-marker disequlibrium, and test for departure from Hardy-Weinberg equilibrium. The package description file and a simple example are append...

...ng genotypes (unordered allele pairs) and haplotypes (ordered allele pairs). Genotypes and haplotypes can be annotated with chromosome, locus, gene, and marker information. Utility functions compute genotype and allele frequencies, flag homozygotes or heterozygotes, flag allele carriers of certain alleles, count the number of a specific allele carried by an individual, extract one or both alleles, estimate and generate confidence intervals for measures of single-marker disequlibrium, and test for departure from Hardy-Weinberg equilibrium. The package description file and a simple example are append...

Hello, I have two data frames, X and Y, with two columns each and different numbers of rows. # creation of data frame X Loc1.alleles <- c(1,5,6,7,8) Loc1.Freq <- c(0.35, 0.15, 0.05, 0.10, 0.35) Loc1 <- cbind( Loc1.alleles,Loc1.Freq) X <- data.frame(Loc1) #creation of data frame Y Loc2.alleles <- c(1,4,6,8) Loc2.Freq <- c(0.35, 0.35, 0.10, 0.20) Loc2 <- cbind(...

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

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

...09 0.0435 0.0435 0.0000 0.0109 0.0543 0.1739 0.0761 0.1413 0.1522 0.1087 0.0870 0.0435 0.0217 0.0109 pop2 0.0213 0.0213 0.0000 0.0000 0.0000 0.0426 0.1702 0.2128 0.1596 0.1809 0.0957 0.0745 0.0106 0.0106 0.0000 0.0000 0.0000 a1,a2,a3 ...... a17 is the frequency of 17 alleles , the sum is 1. I want to test the significance of the distribution of 17 alleles between two populations. How can I do? I want to use chisquare, is is right for these data ? can anyone help me ? Thanks!! luan Yellow Sea Fisheries Research Institute , Chinese Academy of Fishery Sciences , Qing...

Hi everyone, I'm using the function 'HWE.exact' of 'genetics' package to compute p-values of the HWE test. My data set consists of ~600 subjects (cases and controls) typed at ~ 10K SNP markers; the test is applied separately to cases and controls. The genotypes are stored in a list of 'genotype' objects, all.geno, and p-values are calculated inside the loop over all

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.

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)

...details... I made a subset that I called MessWith and it is made up of the first 24 probands and their parents. 2 probands had neither a mother nor a father. Of the remaining, probands, 16 only had one parent. > summary(Genotype.914186) Number of samples typed: 52 (72.2%) Allele Frequency: (2 alleles) Count Proportion 1 73 0.7 2 31 0.3 NA 40 NA Genotype Frequency: Count Proportion 1/1 26 0.5 1/2 21 0.4 2/2 5 0.1 NA 20 NA Heterozygosity (Hu) = 0.4225168 Poly. Inf. Content = 0.3309022 tdt(Genotype.914186, Me...

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 :

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

...2 [5,] 2 0 [6,] 2 0 [7,] 2 0 [8,] 2 0 [9,] 0 2 [10,] NA NA > allele.count(g2) list() If I print the objects I get this > g1 [1] "D/D" "D/I" "D/D" "I/I" "D/D" "D/D" "D/D" "D/D" "I/I" NA Alleles: D I > g2 [1] "1/1" "1/1" "1/1" "1/1" "1/1" "1/1" "1/1" "1/1" "2/2" "1/1" "2/2" "1/1" "1/1" "1/1" Alleles: Clearly g1 and g2 are not exactly the same even...