Package: sim1000G 1.40

Apostolos Dimitromanolakis

sim1000G: Genotype Simulations for Rare or Common Variants Using Haplotypes from 1000 Genomes

Generates realistic simulated genetic data in families or unrelated individuals.

Authors:Apostolos Dimitromanolakis <[email protected]>, Jingxiong Xu <[email protected]>, Agnieszka Krol <[email protected]>, Laurent Briollais <[email protected]>

sim1000G_1.40.tar.gz
sim1000G_1.40.tar.gz(r-4.5-noble)sim1000G_1.40.tar.gz(r-4.4-noble)
sim1000G_1.40.tgz(r-4.4-emscripten)sim1000G_1.40.tgz(r-4.3-emscripten)
sim1000G.pdf |sim1000G.html✨
sim1000G/json (API)

# Install 'sim1000G' in R:
install.packages('sim1000G', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.60 score 1 stars 67 scripts 231 downloads 3 mentions 33 exports 29 dependencies

Last updated 5 years agofrom:fa45ae4611. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-linuxOKNov 10 2024

Exports:computePairIBD1computePairIBD12computePairIBD2createVCFcrossoverCDFvectordownloadGeneticMapgenerateChromosomeRecombinationPositionsgenerateFakeWholeGenomeGeneticMapgenerateRecombinationDistancesgenerateRecombinationDistances_noInterferencegenerateSingleRecombinationVectorgenerateUniformGeneticMapgenerateUnrelatedIndividualsgeneticMapgetCMfromBPloadSimulationnewFamily3generationsnewFamilyWithOffspringnewNuclearFamilypkg.optsplotRegionalGeneticMapprintMatrixreadGeneticMapreadGeneticMapFromFilereadVCFresetSimulationretrieveGenotypessaveSimulationsetRecombinationModelSIMstartSimulationsubsetVCFwritePED

Dependencies:bitbit64clicliprcpp11crayonfansigluehapsimhmslifecyclemagrittrMASSpillarpkgconfigprettyunitsprogressR6readrrlangstringistringrtibbletidyselecttzdbutf8vctrsvroomwithr

sim1000G - Extracting regions from 1000 genomes vcf files for use with sim1000G

Apostolos Dimitromanolakis

Rendered fromExtractingRegionsForSimulation.Rmdusingknitr::rmarkdownon Nov 10 2024.

Last update: 2018-02-18
Started: 2018-02-18

sim1000G: Simulating variant data in families using 1000 genomes haplotypes

Apostolos Dimitromanolakis

Rendered fromSimulatingFamilyData.Rmdusingknitr::rmarkdownon Nov 10 2024.

Last update: 2018-02-18
Started: 2017-08-17

Readme and manuals

Help Manual

Help pageTopics
Simulations of rare/common variants using haplotype data from 1000 genomessim1000G-package sim1000G
Computes pairwise IBD1 for a specific pair of individuals. See function computePairIBD12 for description.computePairIBD1
Computes pairwise IBD1/2 for a specific pair of individualscomputePairIBD12
Computes pairwise IBD2 for a specific pair of individualscomputePairIBD2
Creates a regional vcf file using bcftools to extract a region from 1000 genomes vcf filescreateVCF
Contains recombination model information.crossoverCDFvector
Downloads a genetic map for a particular chromosome under GRCh37 coordinates for use with sim1000G.downloadGeneticMap
Generates a recombination vector arising from one meiotic event. The origin of segments is coded as (0 - haplotype1 , 1 - haplotype2 )generateChromosomeRecombinationPositions
Generates a fake genetic map that spans the whole genome.generateFakeWholeGenomeGeneticMap
Generate inter-recombination distances using a chi-square model. Note this are the distances between two succesive recombination events and not the absolute positions of the events. To generate the locations of the recombination events see the example below.generateRecombinationDistances
Generate recombination distances using a no-interference model.generateRecombinationDistances_noInterference
Genetates a recombination vector arising from one meiotic event. The origin of segments is coded as (0 - haplotype1 , 1 - haplotype2 )generateSingleRecombinationVector
Generates a uniform genetic map.generateUniformGeneticMap
Generates variant data for n unrelated individualsgenerateUnrelatedIndividuals
Holds the genetic map information that is used for simulations.geneticMap
Converts centimorgan position to base-pair. Return a list of centimorgan positions that correspond to the bp vector (in basepairs).getCMfromBP
Load some previously saved simulation data by function saveSimulationloadSimulation
Generates genotype data for a family of 3 generationsnewFamily3generations
Simulates genotypes for 1 family with n offspringnewFamilyWithOffspring
Simulates genotypes for 1 family with 1 offspringnewNuclearFamily
Holds general package optionspkg.opts
Generates a plot of the genetic map for a specified region.plotRegionalGeneticMap
Utility function that prints a matrix. Useful for IBD12 matrices.printMatrix
Reads a genetic map downloaded from the function downloadGeneticMap or reads a genetic map from a specified file. If the argument filename is used then the genetic map is read from the corresponding file. Otherwise, if a chromosome is specified, the genetic map is downloaded for human chromosome using grch37 coordinates.readGeneticMap
Reads a genetic map to be used for simulations. The genetic map should be of a single chromosome and covering the extent of the region to be simulated. Whole chromosome genetic maps can also be used.readGeneticMapFromFile
Read a vcf file, with options to filter out low or high frequency markers.readVCF
Removes all individuals that have been simulated and resets the simulator.resetSimulation
Retrieve a matrix of simulated genotypes for a specific set of individual IDsretrieveGenotypes
Save the data for a simulation for later use. When simulating multiple populations it allows saving and restoring of simulation data for each population.saveSimulation
Set recombination model to either poisson (no interference) or chi-square.setRecombinationModel
Holds data necessary for a simulation.SIM
Starts and initializes the data structures required for a simulation. A VCF file should be read beforehand with the function readVCF.startSimulation
Generate a market subset of a vcf filesubsetVCF
Writes a plink compatible PED/MAP file from the simulated genotypeswritePED