similar to: haplotype and epistasis analysis using 3 or more SNPs?

Hi all, I am working for reconstructing haplotype from individual's SNPs. But I have met a problem that most of paper and software I found are focus on reconstructing haplotype from population's SNPs, rather than individual's SNPs. I wonder is there any R package can be used to solve such problem? Thanks in advance for any information, Gang Chen [[alternative HTML version

Dear All, I'd like to perform adonis (from the vegan package) rather than amova (in ade4) on some haplotype data, as I have crossed factors. Is there a simple way to tweak the source to allow weights (haplotype frequencies) in a similar way to amova? Best Simon

Dear friends - a couple of papers in PNAS (lastly:framework for making better predictions by directly estimating variables' predictivity, Lo et al PNAS 2016; 113:14277-14282) have focused interest on mapping complex traits to multiple loci spread all over the genome. I have been around on the relevant taskview(s) I hope but fail to see that the backward haplotype transmission association

Hi, I'm doing haplotype networks with the package pegas and the script from Jimmy O'Donell's blog. The networks which I obtain are a little ugly and I'd like to change some aspects of their appearance, but I'm just starting with R and I don't know how to do it. I have the following problems: -Some nodes overlap. I increase the scale.ratio but then I get a tiny legend. So

I a using plink on a large SNP dataset with a .map and .ped file. I want to get some sort of file say a list of all the SNPs that plink is saying that I have. ANyideas on how to do this? -- Thanks, Jim. [[alternative HTML version deleted]]

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

Fixes the piglits which check that gl_VertexID includes the base vertex offset: arb_draw_indirect-vertexid elements gl-3.2-basevertex-vertexid Note that this leaves out the original G80, for which this will continue to fail. It could be fixed by passing a driver constbuf value in, but that's beyond the scope of this change. Signed-off-by: Ilia Mirkin <imirkin at alum.mit.edu> Cc:

Hi, Anybody knows a function that can fit haplotype data to a Cox model. I've been searching it in the web without succeed. I use "haplo.stats" package, but unfortunatelly it's not possible to analyse survival data, amb I right?. Thanks in advance. Isaac Subirana (isubirana@imim.es) [[alternative HTML version deleted]]

Hello everyone, I've been trying to adapt a switch emulator to emulate nouveau's compute. We've been told some things like indirect dispatch use the MME in Nouveau, however, looking at NVIDIA's open gpu documentation there's no MME in compute engine since Kepler. https://github.com/NVIDIA/open-gpu-doc/blob/master/classes/compute/clb1c0.h MME for compute should still exist

snpMatrix package is quite nice (read.plink())

Version 1.0 of hapassoc now available from CRAN hapassoc is an R package for likelihood inference of trait associations with SNP haplotypes and other attributes using the EM Algorithm. Recent changes include the addition of anova and logLik methods for the class hapassoc, to allow users to perform likelihood ratio tests of haplotype effects. Other changes include bug-fixes and improvements to

Version 1.0 of hapassoc now available from CRAN hapassoc is an R package for likelihood inference of trait associations with SNP haplotypes and other attributes using the EM Algorithm. Recent changes include the addition of anova and logLik methods for the class hapassoc, to allow users to perform likelihood ratio tests of haplotype effects. Other changes include bug-fixes and improvements to

Dear R-helpers, I am trying to fit my data to a 4-parameter lognormal distribution (aka Johnson Sb dist) with fitdist function from the library(fitdistrplus). So far, I have learnt that with "mle" method it's not always possible to estimate the gamma and delta parameters even if the bounding estimates are "known"/"guessed". Therefore, I tried to fit it with the

I'm trying to: Resample with replacement pairs of distinct rows from a 120 x 65,000 matrix H of 0's and 1's. For each resampled pair sum the resulting 2 x 65,000 matrix by column: 0 1 0 1 ... + 0 0 1 1 ... _______ = 0 1 1 2 ... For each column accumulate the number of 0's, 1's and 2's over the resamples to obtain a 3 x 65,000 matrix G. For those

Hi, The program below work very well. (snps = c('rs621782_G', 'rs8087639_G', 'rs8094221_T', 'rs7227515_A', 'rs537202_C')) Selec = todos[ , colnames(todos) %in% snps] head(Selec) But, I have a data set with 1.000 columns and I need extract 70 to use (like snps in command above). This 70 snps are in a file. So I create a file to extract them with

Hi I am beginner with R I would like to compare the performance of Maximum likelihood Estimator (MLE) and Method of Moment Estimator (MME) effect probability of rejection, p. My MLE is x=rlnorm(10,meanlog = 2, sdlog =5) x xbar=mean(x) ssqrt=var(x) xbar ssqrt #MLE y=log(x) m1=mean(y) s1=var(y) m1 s1 #MME m2=log(xbar^2/sqrt(ssqrt+xbar^2)) s2 = log((ssqrt+xbar^2)/xbar^2) m2

Dear R developers: I am a PHD candidate student in the school of public health of Peking University and my major is genetic epidemiology. I am learning the FAM-MDR algorithm, which is used to detect the gene-gene and gene-environment interactions in the data of pedigree. The codes were written by Tom Cattaert of the University of Liege. The algorithms and the sample datasets are available at

The main patches are from Christoph. Unfortunately they're a little beyond my understanding of all the vertex-related details, but they generally seemed fine. I'm just going to push these unless someone steps up to review them. Christoph Bumiller (2): nvc0: add support for indirect drawing nvc0: fix translate path for PRIM_RESTART_WITH_DRAW_ARRAYS Ilia Mirkin (1): nouveau: check if

I have a solution (actually a few) to this problem, but none are computationally efficient enough to be useful. I'm hoping someone can enlighten me to a better solution. I have data frame of chromosome/position pairs (along with other data for the location). For each pair I need to determine if it is with in a given data frame of ranges. I need to keep only the pairs that are within any of

Dear R-devel, I am writing for help on how I should include parallel sets of data in my package. Brief summary: I am new to using data within packages. I want a user to be able to specify one of two alternative versions of within-package datasets to use, and I want to load just that one. I have a solution that works, but it doesn't seem as simple as it should be from a user's