similar to: loop over large dataset

I have a data frame containing the Id, Mother, Father and Sex from about 10,000 animals in our colony. I am interested in graphing simple family trees for a given subject or small number of subjects. The basic idea is: start with data frame from entire colony and list of index animals. I need to identify all immediate relatives of these index animals and plot the pedigree for them. We're

Hi All, is there any chance of vectorising the two ifelse() statements in the following code: for(i in gp){ new[i,1] = ifelse(srow[i]>0, new[srow[i],zippo[i]], sample(1:100, 1, prob =Y1, rep = T)) new[i,2] = ifelse(drow[i]>0, new[drow[i]>0,zappo[i]], sample(1:100, 1, prob =Y1, rep = T)) } Where I am forced to check if the value of drow and srow are >0 for each line... in

Hi, I have a dataframe that contains pedigree information; that is individual, sire and dam identities as separate columns. It also has date of birth. These identifiers are not numeric, or not sequential. Obviously, an identifier can appear in one or two columns, depending on whether it was a parent or not. These should be consistent. Not all identifiers appear in the individual column - it is

Hi R community, I am new bird to R and moved recently from SAS. I am no means expert on either but very curious learner. So your help crucial for me to learn R. I have already got positive expression. I was trying to fit a mixed model in animal experiment but stuck at simple point. The following similar example is from SAS mixed model pp 212. # data genetic_evaluation <-

Hola a todos, me gustaría realizar una consulta asociada a la generación de valores genéticos del pedigreemm en R. Primero generé el archivo de pedigree incluyendo los parentales para posteriormente estimar la varianza aditiva y los valores genéticos para cada individuo, relacionando los individuos por medio de la matriz de parentesco. Me da todo perfecto, el complemento pedigreemm trabaja muy

Hello, I am trying to make the switch from SAS, and I have a fairly elemental problem with syntax using the nlme package for analyzing mixed models. There was a previous question on this topic posted to this list, so I apologize for redundancy, but I didn't understand the advice given to that inquiry. The model I want to run has the following factors: Host (fixed) Sire (random) Dam

Hi Everyone, I posted a similar question about a week ago, but haven't gotten any replies -- I'm afraid that's because my previous question was too vague. Let me try again with a more specific question, and I hope someone can help. NOTE, I know I should be using the newer lme4 package, I just haven't had a chance to update my version of R yet, so the question below relates

Hola a todos, A partir de los siguientes datos: d <- list(`1` = structure(list(ped = c(1L, 1L, 1L, 1L, 1L, 1L, 1L), id = 1:7, father = c(2L, 0L, 0L, 2L, 2L, 2L, 2L), mother = c(3L, 0L, 0L, 3L, 3L, 3L, 3L), sex = c(2L, 1L, 2L, 2L, 2L, 1L, 2L), affected = c(1L, 2L, 1L, 1L, 2L, 2L, 2L)), row.names = c("1", "2", "3", "4", "5",

Hello, I am building a R-package for Genetics analysis. The accepted data is in pedigree (.ped) file format. To load the data (say CAMP.ped) from "data" directory, I have a function "CAMP.R", which does the job. The package builds successfully in Linux (.tar.gz) and the data loads successfully by "data(CAMP)". However, when I build the package in WINDOWS, the data

I am making the question clear. Please help. > Dear R experts > > I was using kinship package to fit mixed model with kinship matrix. > The package looks like lme4, but I could find a way to extract p-value > out of it. I need to extract is as I need to analyse large number of > variables (> 10000). > > Please help me: > > require(kinship) > > #Generating

Hi Im using the kinship package to draw a pedigree. On my data set this works fine but when i add indivudals to the pedigree i keep getting an error i hope someone can help me! This is the code im using: Data<-read.table("Tree.txt", header=T, sep=",") attach(Data) ped<-pedigree(id, dadid, momid, sex, aff) par(xpd=T) plot.pedigree(ped) This is my data looks like

Dear lists, I want to construct a loop in R, but don't know how to do it. I can do it in SAS, but I prefer in R (which I am hoping I will off SAS for good soon). Could anyone help me to convert the SAS codes to equivalent R codes. Basically, the following codes were written to establish the sire gametes or phases for daughter design for one markers two alleles. Here are the SAS code: do

Announcement: mvtnorm Multivariate Normal and T Distribution mvtnorm implements two R functions for the computation of the multivariate t and normal distribution: pmvt: Computes the the distribution function of the multivariate t distribution for arbitary limits, degrees of freedom and correlation matrices based on algorithms by Genz and Bretz. pmvnorm: Computes the distribution

Announcement: mvtnorm Multivariate Normal and T Distribution mvtnorm implements two R functions for the computation of the multivariate t and normal distribution: pmvt: Computes the the distribution function of the multivariate t distribution for arbitary limits, degrees of freedom and correlation matrices based on algorithms by Genz and Bretz. pmvnorm: Computes the distribution

Dear R mailing list, I have a dataset with genotypes from trios and I would like to infer haplotypes for each mother, father and child. The package that I could find that can do this is tdthap. But when the mother is homozygous (e.g., 2/2) the haplotype is called as not possible to infer (0); I would prefer for it to call the genotype (2). From what I understand it is doing what I would like

Hi, I'm running into a problem subsetting a data frame that I have never encountered before: > dim(chkPd) [1] 3213 6 > df = head(chkPd) > df PN WB Sire Dam MG SEX 601 1001 715349 61710 61702 67 F 969 1001_1 511092 616253 615037 168 F 986 1002_1 511082 616253 623905 168 F 667 1003 715617 61817 61441 67 F

Hello R experts, what follows is my reproducible example: mydata<-structure(list(ped.avg = c(335.9, 110.8, 645.7, 638.9, 1468.1, 126.4, 4811.1, 88.5, 868.5, 656.6, 723.6, 654, 2.8, 15, 14.2, 17.5, 15.4, 112.1, 424.7, 18.3, 19.9, 28.6, 25.6, 23.5, 15.4, 27, 62.1, 15.6, 74.6), ped.erst = c(96, 53.2, 615.2, 616.5, 512.9, 56.2, 1851.8, 57.1, 579.5, 613.2, 601.1, 613.6, 1.3, 6.3, 6.5, 6.1,

Dear R-experts Execuse me for an easy question, but I need help, sorry for that. >From days I have been working with a large dataset, where operations are needed within a component of dataset. Here is my question: I have big dataset where x1:.....x1000 or so. What I need to do is to work on 4 consequite variables to calculate a statistics and output. So far so good. There are more vector

Dear R-helpers, First I apologize if my question is quite simple I have a large datasets which more 100 variables. For a research I need to change all name of variables with add one or more letters on each variables. For example, > data(Pima.tr) > Pima.tr[1:5,] npreg glu bp skin bmi ped age type 1 5 86 68 28 30.2 0.364 24 No 2 7 195 70 33 25.1 0.163 55 Yes 3 5

Dear R experts. I might be missing something obvious. I have been trying to fix this problem for some weeks. Please help. #data ped <- c(rep(1, 4), rep(2, 3), rep(3, 3)) y <- rnorm(10, 8, 2) # variable set 1 M1a <- sample (c(1, 2,3), 10, replace= T) M1b <- sample (c(1, 2,3), 10, replace= T) M1aP1 <- sample (c(1, 2,3), 10, replace= T) M1bP2 <- sample (c(1, 2,3), 10, replace= T)