Showing 57 of total 57 results (show query)
r-computing-lab
BGmisc:An R Package for Extended Behavior Genetics Analysis
Provides functions for behavior genetics analysis, including variance component model identification [Hunter et al. (2021) <doi:10.1007/s10519-021-10055-x>], calculation of relatedness coefficients using path-tracing methods [Wright (1922) <doi:10.1086/279872>; McArdle & McDonald (1984) <doi:10.1111/j.2044-8317.1984.tb00802.x>], inference of relatedness, pedigree conversion, and simulation of multi-generational family data [Lyu et al. (2024) <doi:10.1101/2024.12.19.629449>]. For a full overview, see Garrison et al. (2024) <doi:10.21105/joss.06203>.
Maintained by S. Mason Garrison. Last updated 25 days ago.
38.3 match 1 stars 6.83 score 35 scripts
fabienlaporte
Relatedness:Maximum Likelihood Estimation of Relatedness using EM Algorithm
Inference of relatedness coefficients from a bi-allelic genotype matrix using a Maximum Likelihood estimation, Laporte, F., Charcosset, A. and Mary-Huard, T. (2017) <doi:10.1111/biom.12634>.
Maintained by Fabien Laporte. Last updated 7 years ago.
64.6 match 2.04 score 11 scripts
bioc
GENESIS:GENetic EStimation and Inference in Structured samples (GENESIS): Statistical methods for analyzing genetic data from samples with population structure and/or relatedness
The GENESIS package provides methodology for estimating, inferring, and accounting for population and pedigree structure in genetic analyses. The current implementation provides functions to perform PC-AiR (Conomos et al., 2015, Gen Epi) and PC-Relate (Conomos et al., 2016, AJHG). PC-AiR performs a Principal Components Analysis on genome-wide SNP data for the detection of population structure in a sample that may contain known or cryptic relatedness. Unlike standard PCA, PC-AiR accounts for relatedness in the sample to provide accurate ancestry inference that is not confounded by family structure. PC-Relate uses ancestry representative principal components to adjust for population structure/ancestry and accurately estimate measures of recent genetic relatedness such as kinship coefficients, IBD sharing probabilities, and inbreeding coefficients. Additionally, functions are provided to perform efficient variance component estimation and mixed model association testing for both quantitative and binary phenotypes.
Maintained by Stephanie M. Gogarten. Last updated 2 months ago.
snpgeneticvariabilitygeneticsstatisticalmethoddimensionreductionprincipalcomponentgenomewideassociationqualitycontrolbiocviews
12.2 match 36 stars 10.44 score 342 scripts 1 dependents
magnusdv
ribd:Pedigree-based Relatedness Coefficients
Recursive algorithms for computing various relatedness coefficients, including pairwise kinship, kappa and identity coefficients. Both autosomal and X-linked coefficients are computed. Founders are allowed to be inbred, which enables construction of any given kappa coefficients, as described in Vigeland (2020) <doi:10.1007/s00285-020-01505-x>. In addition to the standard coefficients, 'ribd' also computes a range of lesser-known coefficients, including generalised kinship coefficients, multi-person coefficients and two-locus coefficients (Vigeland, 2023, <doi:10.1093/g3journal/jkac326>). Many features of 'ribd' are available through the online app 'QuickPed' at <https://magnusdv.shinyapps.io/quickped>; see Vigeland (2022) <doi:10.1186/s12859-022-04759-y>.
Maintained by Magnus Dehli Vigeland. Last updated 1 months ago.
inbreeding-coefficientkinshippedigree-analysisrelatedness
19.4 match 6 stars 5.95 score 10 scripts 11 dependents
paballand
EconGeo:Computing Key Indicators of the Spatial Distribution of Economic Activities
Functions to compute a series of indices commonly used in the fields of economic geography, economic complexity, and evolutionary economics to describe the location, distribution, spatial organization, structure, and complexity of economic activities. Functions include basic spatial indicators such as the location quotient, the Krugman specialization index, the Herfindahl or the Shannon entropy indices but also more advanced functions to compute different forms of normalized relatedness between economic activities or network-based measures of economic complexity. Most of the functions use matrix calculus and are based on bipartite (incidence) matrices consisting of region - industry pairs.
Maintained by Pierre-Alexandre Balland. Last updated 2 years ago.
23.3 match 41 stars 4.96 score 44 scriptsbioc
SNPRelate:Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data
Genome-wide association studies (GWAS) are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed an R package SNPRelate to provide a binary format for single-nucleotide polymorphism (SNP) data in GWAS utilizing CoreArray Genomic Data Structure (GDS) data files. The GDS format offers the efficient operations specifically designed for integers with two bits, since a SNP could occupy only two bits. SNPRelate is also designed to accelerate two key computations on SNP data using parallel computing for multi-core symmetric multiprocessing computer architectures: Principal Component Analysis (PCA) and relatedness analysis using Identity-By-Descent measures. The SNP GDS format is also used by the GWASTools package with the support of S4 classes and generic functions. The extended GDS format is implemented in the SeqArray package to support the storage of single nucleotide variations (SNVs), insertion/deletion polymorphism (indel) and structural variation calls in whole-genome and whole-exome variant data.
Maintained by Xiuwen Zheng. Last updated 5 months ago.
infrastructuregeneticsstatisticalmethodprincipalcomponentbioinformaticsgds-formatpcasimdsnpopenblascpp
6.5 match 104 stars 12.69 score 1.6k scripts 18 dependentsmagnusdv
ibdsim2:Simulation of Chromosomal Regions Shared by Family Members
Simulation of segments shared identical-by-descent (IBD) by pedigree members. Using sex specific recombination rates along the human genome (Halldorsson et al. (2019) <doi:10.1126/science.aau1043>), phased chromosomes are simulated for all pedigree members. Applications include calculation of realised relatedness coefficients and IBD segment distributions. 'ibdsim2' is part of the 'pedsuite' collection of packages for pedigree analysis. A detailed presentation of the 'pedsuite', including a separate chapter on 'ibdsim2', is available in the book 'Pedigree analysis in R' (Vigeland, 2021, ISBN:9780128244302). A 'Shiny' app for visualising and comparing IBD distributions is available at <https://magnusdv.shinyapps.io/ibdsim2-shiny/>.
Maintained by Magnus Dehli Vigeland. Last updated 15 days ago.
identity-by-descentrelatednesssimulationcpp
14.5 match 5 stars 5.00 score 19 scripts 1 dependents
eppicenter
dcifer:Genetic Relatedness Between Polyclonal Infections
An implementation of Dcifer (Distance for complex infections: fast estimation of relatedness), an identity by descent (IBD) based method to calculate genetic relatedness between polyclonal infections from biallelic and multiallelic data. The package includes functions that format and preprocess the data, implement the method, and visualize the results. Gerlovina et al. (2022) <doi:10.1093/genetics/iyac126>.
Maintained by Inna Gerlovina. Last updated 10 months ago.
13.5 match 5 stars 4.57 score 15 scripts
jiscah
sequoia:Pedigree Inference from SNPs
Multi-generational pedigree inference from incomplete data on hundreds of SNPs, including parentage assignment and sibship clustering. See Huisman (2017) (<DOI:10.1111/1755-0998.12665>) for more information.
Maintained by Jisca Huisman. Last updated 9 months ago.
pedigreepedigree-reconstructionpedigreessequoiasnpsnp-datafortran
7.0 match 26 stars 7.40 score 79 scriptsmagnusdv
verbalisr:Describe Pedigree Relationships in Words
Describe in words the genealogical relationship between two members of a given pedigree, using the algorithm in Vigeland (2022) <doi:10.1186/s12859-022-04759-y>. 'verbalisr' is part of the 'pedsuite' collection of packages for pedigree analysis. For a demonstration of 'verbalisr', see the online app 'QuickPed' at <https://magnusdv.shinyapps.io/quickped>.
Maintained by Magnus Dehli Vigeland. Last updated 3 days ago.
pedigree-analysisrelatednessrelationship-detection
10.0 match 1 stars 4.92 score 7 scripts 8 dependentsmagnusdv
forrel:Forensic Pedigree Analysis and Relatedness Inference
Forensic applications of pedigree analysis, including likelihood ratios for relationship testing, general relatedness inference, marker simulation, and power analysis. 'forrel' is part of the 'pedsuite', a collection of packages for pedigree analysis, further described in the book 'Pedigree Analysis in R' (Vigeland, 2021, ISBN:9780128244302). Several functions deal specifically with power analysis in missing person cases, implementing methods described in Vigeland et al. (2020) <doi:10.1016/j.fsigen.2020.102376>. Data import from the 'Familias' software (Egeland et al. (2000) <doi:10.1016/S0379-0738(00)00147-X>) is supported through the 'pedFamilias' package.
Maintained by Magnus Dehli Vigeland. Last updated 6 days ago.
5.5 match 11 stars 6.98 score 63 scripts 7 dependents
matthewwolak
nadiv:(Non)Additive Genetic Relatedness Matrices
Constructs (non)additive genetic relationship matrices, and their inverses, from a pedigree to be used in linear mixed effect models (A.K.A. the 'animal model'). Also includes other functions to facilitate the use of animal models. Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<https://vsni.co.uk/software/asreml>).
Maintained by Matthew Wolak. Last updated 10 months ago.
4.7 match 20 stars 7.13 score 151 scripts 3 dependents
marsicofl
mispitools:Missing Person Identification Tools
An open source software package written in R statistical language. It consists of a set of decision-making tools to conduct missing person searches. Particularly, it allows computing optimal LR threshold for declaring potential matches in DNA-based database search. More recently 'mispitools' incorporates preliminary investigation data based LRs. Statistical weight of different traces of evidence such as biological sex, age and hair color are presented. For citing mispitools please use the following references: Marsico and Caridi, 2023 <doi:10.1016/j.fsigen.2023.102891> and Marsico, Vigeland et al. 2021 <doi:10.1016/j.fsigen.2021.102519>.
Maintained by Franco Marsico. Last updated 3 months ago.
4.8 match 35 stars 6.74 score 19 scripts 1 dependents
kenhanscombe
ukbtools:Manipulate and Explore UK Biobank Data
A set of tools to create a UK Biobank <http://www.ukbiobank.ac.uk/> dataset from a UKB fileset (.tab, .r, .html), visualize primary demographic data for a sample subset, query ICD diagnoses, retrieve genetic metadata, read and write standard file formats for genetic analyses.
Maintained by Ken Hanscombe. Last updated 2 years ago.
4.0 match 101 stars 6.78 score 118 scripts
mikldk
DNAtools:Tools for Analysing Forensic Genetic DNA Data
Computationally efficient tools for comparing all pairs of profiles in a DNA database. The expectation and covariance of the summary statistic is implemented for fast computing. Routines for estimating proportions of close related individuals are available. The use of wildcards (also called F- designation) is implemented. Dedicated functions ease plotting the results. See Tvedebrink et al. (2012) <doi:10.1016/j.fsigen.2011.08.001>. Compute the distribution of the numbers of alleles in DNA mixtures. See Tvedebrink (2013) <doi:10.1016/j.fsigss.2013.10.142>.
Maintained by Mikkel Meyer Andersen. Last updated 2 years ago.
4.1 match 6.00 score 28 scripts
bowenwang7
rres:Realized Relatedness Estimation and Simulation
Functions for studying realized genetic relatedness between people. Users will be able to simulate inheritance patterns given pedigree structures, generate SNP marker data given inheritance patterns, and estimate realized relatedness between pairs of individuals using SNP marker data. See Wang (2017) <doi:10.1534/genetics.116.197004>. This work was supported by National Institutes of Health grants R37 GM-046255.
Maintained by Bowen Wang. Last updated 7 years ago.
7.9 match 2.95 score 18 scriptseppicenter
moire:Multiplicity of Infection and Allele Frequency Recovery from Noisy Polyallelic Genetics Data
A Markov Chain Monte Carlo (MCMC) based approach to Bayesian estimation of individual level multiplicity of infection, within host relatedness, and population allele frequencies from polyallelic genetic data.
Maintained by Maxwell Murphy. Last updated 4 months ago.
4.3 match 7 stars 5.14 score 22 scripts
piyalkarum
rCNV:Detect Copy Number Variants from SNPs Data
Functions in this package will import filtered variant call format (VCF) files of SNPs data and generate data sets to detect copy number variants, visualize them and do downstream analyses with copy number variants(e.g. Environmental association analyses).
Maintained by Piyal Karunarathne. Last updated 14 days ago.
cnv-analysiscopy-number-variationgene-duplicationgeneticsgenomicslandscape-geneticssnpscpp
5.0 match 6 stars 4.26 score 4 scripts
highlanderlab
SIMplyBee:'AlphaSimR' Extension for Simulating Honeybee Populations and Breeding Programmes
An extension of the 'AlphaSimR' package (<https://cran.r-project.org/package=AlphaSimR>) for stochastic simulations of honeybee populations and breeding programmes. 'SIMplyBee' enables simulation of individual bees that form a colony, which includes a queen, fathers (drones the queen mated with), virgin queens, workers, and drones. Multiple colony can be merged into a population of colonies, such as an apiary or a whole country of colonies. Functions enable operations on castes, colony, or colonies, to ease 'R' scripting of whole populations. All 'AlphaSimR' functionality with respect to genomes and genetic and phenotype values is available and further extended for honeybees, including haplo-diploidy, complementary sex determiner locus, colony events (swarming, supersedure, etc.), and colony phenotype values.
Maintained by Jana Obลกteter. Last updated 6 months ago.
3.3 match 2 stars 6.24 score 18 scriptsbioc
GWASTools:Tools for Genome Wide Association Studies
Classes for storing very large GWAS data sets and annotation, and functions for GWAS data cleaning and analysis.
Maintained by Stephanie M. Gogarten. Last updated 5 months ago.
snpgeneticvariabilityqualitycontrolmicroarray
1.9 match 17 stars 10.50 score 396 scripts 5 dependentsbioc
SeqArray:Data Management of Large-Scale Whole-Genome Sequence Variant Calls
Data management of large-scale whole-genome sequencing variant calls with thousands of individuals: genotypic data (e.g., SNVs, indels and structural variation calls) and annotations in SeqArray GDS files are stored in an array-oriented and compressed manner, with efficient data access using the R programming language.
Maintained by Xiuwen Zheng. Last updated 11 days ago.
infrastructuredatarepresentationsequencinggeneticsbioinformaticsgds-formatsnpsnvweswgscpp
1.5 match 45 stars 12.08 score 1.1k scripts 9 dependents
jonotuke
BREADR:Estimates Degrees of Relatedness (Up to the Second Degree) for Extreme Low-Coverage Data
The goal of the package is to provide an easy-to-use method for estimating degrees of relatedness (up to the second degree) for extreme low-coverage data. The package also allows users to quantify and visualise the level of confidence in the estimated degrees of relatedness.
Maintained by Jono Tuke. Last updated 25 days ago.
3.6 match 8 stars 4.45 score 4 scripts
jarrodhadfield
MCMCglmm:MCMC Generalised Linear Mixed Models
Fits Multivariate Generalised Linear Mixed Models (and related models) using Markov chain Monte Carlo techniques (Hadfield 2010 J. Stat. Soft.).
Maintained by Jarrod Hadfield. Last updated 3 months ago.
1.8 match 2 stars 8.83 score 1.2k scripts 13 dependentsbioc
LymphoSeq:Analyze high-throughput sequencing of T and B cell receptors
This R package analyzes high-throughput sequencing of T and B cell receptor complementarity determining region 3 (CDR3) sequences generated by Adaptive Biotechnologies' ImmunoSEQ assay. Its input comes from tab-separated value (.tsv) files exported from the ImmunoSEQ analyzer.
Maintained by David Coffey. Last updated 5 months ago.
softwaretechnologysequencingtargetedresequencingalignmentmultiplesequencealignment
3.6 match 4.00 score 4 scripts
wtkr
heritability:Marker-Based Estimation of Heritability Using Individual Plant or Plot Data
Implements marker-based estimation of heritability when observations on genetically identical replicates are available. These can be either observations on individual plants or plot-level data in a field trial. Heritability can then be estimated using a mixed model for the individual plant or plot data. For comparison, also mixed-model based estimation using genotypic means and estimation of repeatability with ANOVA are implemented. For illustration the package contains several datasets for the model species Arabidopsis thaliana.
Maintained by Willem Kruijer. Last updated 2 years ago.
6.8 match 2 stars 1.90 score 40 scripts
pbreheny
plmmr:Penalized Linear Mixed Models for Correlated Data
Fits penalized linear mixed models that correct for unobserved confounding factors. 'plmmr' infers and corrects for the presence of unobserved confounding effects such as population stratification and environmental heterogeneity. It then fits a linear model via penalized maximum likelihood. Originally designed for the multivariate analysis of single nucleotide polymorphisms (SNPs) measured in a genome-wide association study (GWAS), 'plmmr' eliminates the need for subpopulation-specific analyses and post-analysis p-value adjustments. Functions for the appropriate processing of 'PLINK' files are also supplied. For examples, see the package homepage. <https://pbreheny.github.io/plmmr/>.
Maintained by Patrick J. Breheny. Last updated 12 days ago.
2.0 match 4 stars 6.31 score 10 scriptsbioc
SeqSQC:A bioconductor package for sample quality check with next generation sequencing data
The SeqSQC is designed to identify problematic samples in NGS data, including samples with gender mismatch, contamination, cryptic relatedness, and population outlier.
Maintained by Qian Liu. Last updated 5 months ago.
experiment datahomo_sapiens_datasequencing dataproject1000genomesgenome
2.3 match 5.38 score 2 scriptsbioc
minet:Mutual Information NETworks
This package implements various algorithms for inferring mutual information networks from data.
Maintained by Patrick E. Meyer. Last updated 5 months ago.
microarraygraphandnetworknetworknetworkinferencecpp
1.9 match 6.15 score 114 scripts 16 dependents
evolandeco
evesim:Evolution Emulator: Species Diversification under an Evolutionary Relatedness Dependent Scenario
Evolutionary relatedness dependent diversification simulation powered by the 'Rcpp' back-end 'SimTable'.
Maintained by Tianjian Qin. Last updated 3 days ago.
3.4 match 3.40 score 5 scripts
sales-lab
parmigene:Parallel Mutual Information Estimation for Gene Network Reconstruction
Parallel estimation of the mutual information based on entropy estimates from k-nearest neighbors distances and algorithms for the reconstruction of gene regulatory networks (Sales et al, 2011 <doi:10.1093/bioinformatics/btr274>).
Maintained by Gabriele Sales. Last updated 5 months ago.
1.9 match 5 stars 6.06 score 38 scripts 4 dependentsbioc
GeneticsPed:Pedigree and genetic relationship functions
Classes and methods for handling pedigree data. It also includes functions to calculate genetic relationship measures as relationship and inbreeding coefficients and other utilities. Note that package is not yet stable. Use it with care!
Maintained by David Henderson. Last updated 5 months ago.
2.9 match 3.86 score 12 scripts
aursiber
LDcorSV:Linkage Disequilibrium Corrected by the Structure and the Relatedness
Four measures of linkage disequilibrium are provided: the usual r^2 measure, the r^2_S measure (r^2 corrected by the structure sample), the r^2_V (r^2 corrected by the relatedness of genotyped individuals), the r^2_VS measure (r^2 corrected by both the relatedness of genotyped individuals and the structure of the sample).
Maintained by Aurรฉlie Siberchicot. Last updated 5 years ago.
3.8 match 2.81 score 13 scripts
rdinnager
slimr:Create, Run and Post-Process 'SLiM' Population Genetics Forward Simulations
Lets you write 'SLiM' scripts (population genomics simulation) using your favourite R IDE, using a syntax as close as possible to the original 'SLiM' language. It offer many tools to manipulate those scripts, as well as run them in the 'SLiM' software from R, as well as capture and post-process their output, after or even during a simulation.
Maintained by Russell Dinnage. Last updated 4 months ago.
2.0 match 8 stars 4.70 score 42 scripts
jangraffelman
Jacquard:Estimation of Jacquard's Genetic Identity Coefficients
Contains procedures to estimate the nine condensed Jacquard genetic identity coefficients (Jacquard, 1974) <doi:10.1007/978-3-642-88415-3> by constrained least squares (Graffelman et al., 2024) <doi:10.1101/2024.03.25.586682> and by the method of moments (Csuros, 2014) <doi:10.1016/j.tpb.2013.11.001>. These procedures require previous estimation of the allele frequencies. Functions are supplied that estimate relationship parameters that derive from the Jacquard coefficients, such as individual inbreeding coefficients and kinship coefficients.
Maintained by Jan Graffelman. Last updated 6 months ago.
4.6 match 2.00 score
fboehm
gemma2:GEMMA Multivariate Linear Mixed Model
Fits a multivariate linear mixed effects model that uses a polygenic term, after Zhou & Stephens (2014) (<https://www.nature.com/articles/nmeth.2848>). Of particular interest is the estimation of variance components with restricted maximum likelihood (REML) methods. Genome-wide efficient mixed-model association (GEMMA), as implemented in the package 'gemma2', uses an expectation-maximization algorithm for variance components inference for use in quantitative trait locus studies.
Maintained by Frederick Boehm. Last updated 4 years ago.
em-algorithmgeneticsmixed-models
1.7 match 13 stars 5.29 score 10 scripts 1 dependents
green-striped-gecko
dartR.captive:Analysing 'SNP' Data to Support Captive Breeding
Functions are provided that facilitate the analysis of SNP (single nucleotide polymorphism) data to answer questions regarding captive breeding and relatedness between individuals. 'dartR.captive' is part of the 'dartRverse' suit of packages. Gruber et al. (2018) <doi:10.1111/1755-0998.12745>. Mijangos et al. (2022) <doi:10.1111/2041-210X.13918>.
Maintained by Bernd Gruber. Last updated 28 days ago.
4.5 match 1 stars 2.00 score 3 scripts
emilmip
LTFHPlus:Implementation of LT-FH++
Implementation of LT-FH++, an extension of the liability threshold family history (LT-FH) model. LT-FH++ uses a Gibbs sampler for sampling from the truncated multivariate normal distribution and allows for flexible family structures. LT-FH++ was first described in Pedersen, Emil M., et al. (2022) <https://pure.au.dk/ws/portalfiles/portal/353346245/> as an extension to LT-FH with more flexible family structures, and again as the age-dependent liability threshold (ADuLT) model Pedersen, Emil M., et al. (2023) <https://www.nature.com/articles/s41467-023-41210-z> as an alternative to traditional time-to-event genome-wide association studies, where family history was not considered.
Maintained by Emil Michael Pedersen. Last updated 9 months ago.
1.9 match 10 stars 4.66 score 23 scripts
wviechtb
metafor:Meta-Analysis Package for R
A comprehensive collection of functions for conducting meta-analyses in R. The package includes functions to calculate various effect sizes or outcome measures, fit equal-, fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots (e.g., forest, funnel, radial, L'Abbe, Baujat, bubble, and GOSH plots). For meta-analyses of binomial and person-time data, the package also provides functions that implement specialized methods, including the Mantel-Haenszel method, Peto's method, and a variety of suitable generalized linear (mixed-effects) models (i.e., mixed-effects logistic and Poisson regression models). Finally, the package provides functionality for fitting meta-analytic multivariate/multilevel models that account for non-independent sampling errors and/or true effects (e.g., due to the inclusion of multiple treatment studies, multiple endpoints, or other forms of clustering). Network meta-analyses and meta-analyses accounting for known correlation structures (e.g., due to phylogenetic relatedness) can also be conducted. An introduction to the package can be found in Viechtbauer (2010) <doi:10.18637/jss.v036.i03>.
Maintained by Wolfgang Viechtbauer. Last updated 3 days ago.
meta-analysismixed-effectsmultilevel-modelsmultivariate
0.5 match 246 stars 16.30 score 4.9k scripts 92 dependentsbioc
MetNet:Inferring metabolic networks from untargeted high-resolution mass spectrometry data
MetNet contains functionality to infer metabolic network topologies from quantitative data and high-resolution mass/charge information. Using statistical models (including correlation, mutual information, regression and Bayes statistics) and quantitative data (intensity values of features) adjacency matrices are inferred that can be combined to a consensus matrix. Mass differences calculated between mass/charge values of features will be matched against a data frame of supplied mass/charge differences referring to transformations of enzymatic activities. In a third step, the two levels of information are combined to form a adjacency matrix inferred from both quantitative and structure information.
Maintained by Thomas Naake. Last updated 5 months ago.
immunooncologymetabolomicsmassspectrometrynetworkregression
1.7 match 4.70 score 1 scripts
evolecolgroup
tidypopgen:Tidy Population Genetics
We provide a tidy grammar of population genetics, facilitating the manipulation and analysis of data on biallelic single nucleotide polymorphisms (SNPs).
Maintained by Andrea Manica. Last updated 5 days ago.
1.3 match 4 stars 5.83 score 8 scripts
juliengamartin
pedtricks:Visualize, Summarize and Simulate Data from Pedigrees
Sensitivity and power analysis, for calculating statistics describing pedigrees from wild populations, and for visualizing pedigrees. This is a reboot of the methods developped by Morrissey and Wilson (2010) <doi: 10.1111/j.1755-0998.2009.02817.x>
Maintained by Julien Martin. Last updated 6 months ago.
1.8 match 2 stars 4.08 score 1 scripts
cran
cluster.datasets:Cluster Analysis Data Sets
A collection of data sets for teaching cluster analysis.
Maintained by Frederick Novomestky. Last updated 11 years ago.
3.5 match 2.00 score
mhunter1
EasyMx:Easy Model-Builder Functions for 'OpenMx'
Utilities for building certain kinds of common matrices and models in the extended structural equation modeling package, 'OpenMx'.
Maintained by Michael D. Hunter. Last updated 2 years ago.
2.0 match 2.32 score 21 scripts
tpook92
MoBPS:Modular Breeding Program Simulator
Framework for the simulation framework for the simulation of complex breeding programs and compare their economic and genetic impact. The package is also used as the background simulator for our a web-based interface <http:www.mobps.de>. Associated publication: Pook et al. (2020) <doi:10.1534/g3.120.401193>.
Maintained by Torsten Pook. Last updated 3 years ago.
1.9 match 2.35 score 45 scripts
gbradburd
conStruct:Models Spatially Continuous and Discrete Population Genetic Structure
A method for modeling genetic data as a combination of discrete layers, within each of which relatedness may decay continuously with geographic distance. This package contains code for running analyses (which are implemented in the modeling language 'rstan') and visualizing and interpreting output. See the paper for more details on the model and its utility.
Maintained by Gideon Bradburd. Last updated 1 years ago.
0.5 match 35 stars 8.39 score 70 scripts
hanchenphd
GMMAT:Generalized Linear Mixed Model Association Tests
Perform association tests using generalized linear mixed models (GLMMs) in genome-wide association studies (GWAS) and sequencing association studies. First, GMMAT fits a GLMM with covariate adjustment and random effects to account for population structure and familial or cryptic relatedness. For GWAS, GMMAT performs score tests for each genetic variant as proposed in Chen et al. (2016) <DOI:10.1016/j.ajhg.2016.02.012>. For candidate gene studies, GMMAT can also perform Wald tests to get the effect size estimate for each genetic variant. For rare variant analysis from sequencing association studies, GMMAT performs the variant Set Mixed Model Association Tests (SMMAT) as proposed in Chen et al. (2019) <DOI:10.1016/j.ajhg.2018.12.012>, including the burden test, the sequence kernel association test (SKAT), SKAT-O and an efficient hybrid test of the burden test and SKAT, based on user-defined variant sets.
Maintained by Han Chen. Last updated 1 years ago.
openblaszlibbzip2libzstdlibdeflatecpp
0.5 match 38 stars 8.34 score 96 scripts 2 dependents
bioc
goSTAG:A tool to use GO Subtrees to Tag and Annotate Genes within a set
Gene lists derived from the results of genomic analyses are rich in biological information. For instance, differentially expressed genes (DEGs) from a microarray or RNA-Seq analysis are related functionally in terms of their response to a treatment or condition. Gene lists can vary in size, up to several thousand genes, depending on the robustness of the perturbations or how widely different the conditions are biologically. Having a way to associate biological relatedness between hundreds and thousands of genes systematically is impractical by manually curating the annotation and function of each gene. Over-representation analysis (ORA) of genes was developed to identify biological themes. Given a Gene Ontology (GO) and an annotation of genes that indicate the categories each one fits into, significance of the over-representation of the genes within the ontological categories is determined by a Fisher's exact test or modeling according to a hypergeometric distribution. Comparing a small number of enriched biological categories for a few samples is manageable using Venn diagrams or other means for assessing overlaps. However, with hundreds of enriched categories and many samples, the comparisons are laborious. Furthermore, if there are enriched categories that are shared between samples, trying to represent a common theme across them is highly subjective. goSTAG uses GO subtrees to tag and annotate genes within a set. goSTAG visualizes the similarities between the over-representation of DEGs by clustering the p-values from the enrichment statistical tests and labels clusters with the GO term that has the most paths to the root within the subtree generated from all the GO terms in the cluster.
Maintained by Brian D. Bennett. Last updated 5 months ago.
geneexpressiondifferentialexpressiongenesetenrichmentclusteringmicroarraymrnamicroarrayrnaseqvisualizationgoimmunooncology
0.5 match 4.30 score 1 scriptsmagnusdv
pedbuildr:Pedigree Reconstruction
Reconstruct pedigrees from genotype data, by optimising the likelihood over all possible pedigrees subject to given restrictions. Tailor-made plots facilitate evaluation of the output. This package is part of the 'pedsuite' ecosystem for pedigree analysis. In particular, it imports 'pedprobr' for calculating pedigree likelihoods and 'forrel' for estimating pairwise relatedness.
Maintained by Magnus Dehli Vigeland. Last updated 2 months ago.
0.5 match 2 stars 3.78 score 7 scripts 1 dependents
wenlongren
ScoreEB:Score Test Integrated with Empirical Bayes for Association Study
Perform association test within linear mixed model framework using score test integrated with empirical bayes for genome-wide association study. Firstly, score test was conducted for each single nucleotide polymorphism (SNP) under linear mixed model framework, taking into account the genetic relatedness and population structure. And then all the potentially associated SNPs were selected with a less stringent criterion. Finally, all the selected SNPs were performed empirical bayes in a multi-locus model to identify the true quantitative trait nucleotide (QTN).
Maintained by Wenlong Ren. Last updated 3 years ago.
0.5 match 2 stars 3.00 score 1 scriptscran
PQLseq:Efficient Mixed Model Analysis of Count Data in Large-Scale Genomic Sequencing Studies
An efficient tool designed for differential analysis of large-scale RNA sequencing (RNAseq) data and Bisulfite sequencing (BSseq) data in the presence of individual relatedness and population structure. 'PQLseq' first fits a Generalized Linear Mixed Model (GLMM) with adjusted covariates, predictor of interest and random effects to account for population structure and individual relatedness, and then performs Wald tests for each gene in RNAseq or site in BSseq.
Maintained by Jiaqiang Zhu. Last updated 4 years ago.
0.8 match 1.60 score
kenstoyama
JNplots:Visualize Outputs from the 'Johnson-Neyman' Technique
Aids in the calculation and visualization of regions of non-significance using the 'Johnson-Neyman' technique and its extensions as described by Bauer and Curran (2005) <doi:10.1207/s15327906mbr4003_5> to assess the influence of categorical and continuous moderators. Allows correcting for phylogenetic relatedness.
Maintained by Ken Toyama. Last updated 1 years ago.
0.5 match 2.00 score 4 scripts
xiaoran831213
plinkFile:'PLINK' (and 'GCTA') File Helpers
reads/write binary genotype file compatable with 'PLINK' <https://www.cog-genomics.org/plink/1.9/input#bed> into/from a R matrix; traverse genotype data one windows of variants at a time, like apply() or a for loop; reads/writes genotype relatedness/kinship matrices created by 'PLINK' <https://www.cog-genomics.org/plink/1.9/distance#make_rel> or 'GCTA' <https://cnsgenomics.com/software/gcta/#MakingaGRM> into/from a R square matrix. It is best used for bringing data produced by 'PLINK' and 'GCTA' into R workflow.
Maintained by Xiaoran Tong. Last updated 3 years ago.
0.5 match 2.00 score 2 scripts