similar to: Pedigreemm

Hi, I'm trying to build a mixed-effects model in which I'd like to include either a distance matrix or a phylogenetic tree as a random effect. The troubles I've had are that: 1. Function lmer() in package lme4 only accepts a data frame column as a random factor and not a distance matrix. 2. Function MCMCglmm() in package MCMCglmm only accepts a rooted and ultrametric phylogenetic

Why doesn't this work? > samples$geno <- as.data.frame(sapply(yo, toupper), col.names="geno") > samples quant_samples age sapply(yo, toupper) E11.5 F20het BA40 E11.5 F20het BA40 E11.5 F20HET E11.5 F20het BA45 E11.5 F20het BA45 E11.5 F20HET

Wait. Now I'm really confused. > > head(samples) quant_samples age sapply(yo, toupper) E11.5 F20het BA40 E11.5 F20het BA40 E11.5 F20HET E11.5 F20het BA45 E11.5 F20het BA45 E11.5 F20HET E11.5 F20het BB84 E11.5 F20het BB84 E11.5 F20HET E11.5 F9.20DKO KTr3 E11.5 F9.20DKO KTr3 E11.5 F9.20DKO E11.5

I wish to make modifications to the plot.pedigree function in the kinship package. My attempts to contact the maintainer have been unsuccessful, but my question is general, so specifics of the kinship package might not be an issue. My first attempt was to make a new function Plot.pedigree in the .GlobalEnv which mostly achieved what I wanted to. However, I'm sure that's not the tidiest

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

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",

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

Hello! I am building a package, which includes also one Fortran subroutine, which works fine if I compile it as a shared library and load it into R via dyn.load(). However, when I launch R CMD check it doesn't stop with checking examples. It's just doing and doing ... I pasted the whole output from R CMD check. Does anyone have any suggestions? I'm still using R 2.0.1.

I want to implement a unique category tree per user in my system, and I was hoping to use "acts_as_tree" on my category model. It seems as if acts_as_tree makes the assumption that the entire table the model is off of is one large tree. I actually want each user to have their own category trees all stored in the category table so I need it to scope off of the user_id.

Hello, I have a tree structure that needs to be converted into a nested set. A great deal of work has already been done on the tree items, so maintaining the integrity of the id''s is mandatory. However I need the ability to access entire branches of the tree, which is what Nested set does. Does anyone have any suggestions on how to efficiently transfer the tree to the nested set and

I'm currently packaging up some of the kinship matrix routines more formally, these are used in coxme when dealing with family correlation structures. One of my test programs exercises error conditions, i.e., it purposely feeds particular types of invalid pedigree data in to see if the right error message results. So there are comment-action pairs # the next line should generate a

Dear R Support Team, I hope this email finds you well. I am writing to inquire about the specific R packages that would best suit our academic research project, which involves analyses in various fields. We are particularly interested in the following areas: Epidemiology Analysis: We are aware that packages like epiR, survival, and epitools exist for epidemiological analysis. Could you please

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

Hello, There is a CRAN Task View: Epidemiology that should be or have what you are looking for. [1] https://CRAN.R-project.org/view=Epidemiology Hope this helps, Rui Barradas ?s 06:29 de 19/09/2024, Aleena Shaji escreveu: > Dear R Support Team, > > I hope this email finds you well. > > I am writing to inquire about the specific R packages that would best suit > our

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'm looking for a histogram variant in which data points are plotted as labelled rectangles 'piled up' to form a histogram. I've posted an example at https://www.dropbox.com/s/ozi8bhdn5kqaufm/labelled_histogram.png?dl=0 It seems to have a long pedigree, as I see it (as in this example) in documents going back beyond the '80s. But I've not seen it in recent textbooks. So it

Hi, You should look at Pinheiro and Bates (2000) Mixed-effects models in S and S-Plus. It describes how to format the correlation matrix to pass to functions lme and gls. Basically, the correlation matrix has to be one of the corStruct classes, probably corSymm for your example. So in the call to lme (or gls if you really have no random effects), use something like:

Hello, I did a pca with over 200000 snps for 340 observations (ids). If I plot the eigenvectors (called rotation in prcomp) 2,3 and 4 (e.g. plot (rotation[,2]) I see a strange "column" in my data (see attachment). I suggest it is an artefact (but of what?). Suggestion: I used prcomp this way: prcomp (mat), where mat is a matrix with the column means already substracted followed by a

Hi All, I'd like to ask for a few clarifications. I am doing some calculations over some biggish datasets. One has ~ 23000 rows, and 6 columns, the other has ~620000 rows and 6 columns. I am using these datasets to perform a simulation of of haplotype coalescence over a pedigree (the datestes themselves are pedigree information). I created a new dataset (same number of rows as the pedigree

I have library in development with a function that works when called from the top level, but fails under R CMD check. The paricular line of failure is rsum <- rowSums(kmat>0) where kmat is a dsCMatrix object. I'm currently stumped and looking for some ideas. I've created a stripped down library "ktest" that has only 3 functions: pedigree.R to create a pedigree or