Package: poolABC 1.0.0.9000

João Carvalho

poolABC: Approximate Bayesian Computation with Pooled Sequencing Data

Provides functions to simulate Pool-seq data under models of demographic formation and to import Pool-seq data from real populations. Implements two ABC algorithms for performing parameter estimation and model selection using Pool-seq data. Cross-validation can also be performed to assess the accuracy of ABC estimates and model choice. Carvalho et al., (2022) <doi:10.1111/1755-0998.13834>.

Authors:João Carvalho [aut, cre, cph], Vítor Sousa [aut]

poolABC_1.0.0.9000.tar.gz
poolABC_1.0.0.9000.zip(r-4.5)poolABC_1.0.0.9000.zip(r-4.4)poolABC_1.0.0.9000.zip(r-4.3)
poolABC_1.0.0.9000.tgz(r-4.4-any)poolABC_1.0.0.9000.tgz(r-4.3-any)
poolABC_1.0.0.9000.tar.gz(r-4.5-noble)poolABC_1.0.0.9000.tar.gz(r-4.4-noble)
poolABC_1.0.0.9000.tgz(r-4.4-emscripten)poolABC_1.0.0.9000.tgz(r-4.3-emscripten)
poolABC.pdf |poolABC.html✨
poolABC/json (API)
NEWS

# Install 'poolABC' in R:

install.packages('poolABC', repos = c('https://vsousa.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/joao-mcarvalho/poolabc/issues

Datasets:

limits - Matrix of prior limits
myparams - Matrix of simulated parameter values
params - Matrix of simulated parameter values
rc1 - Data frame with an example of observed data
rc2 - Data frame with an example of observed data
sumstats - Matrix of summary statistics computed from simulated data

On CRAN:

3.70 score 1 stars 3 scripts 119 downloads 72 exports 46 dependencies

Last updated 1 years agofrom:549505edc9. Checks:OK: 5 NOTE: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 27 2024
R-4.5-win	NOTE	Oct 27 2024
R-4.5-linux	NOTE	Oct 27 2024
R-4.4-win	OK	Oct 27 2024
R-4.4-mac	OK	Oct 27 2024
R-4.3-win	OK	Oct 27 2024
R-4.3-mac	OK	Oct 27 2024

Exports:abba ABC baba BTmatrix checkCoverage checkMajor checkMissing cleanData cmd2pops cmdParallel cmdSingle createHeader createParams D.stat D.statPool error_modelSel errorABC euclidean exclusive Expected_Het filterData fixed forceLocus getFst getmode Het_Between importContigs importData index.rejABC indexSNPs inverse_trans meanExpected_Het mergepost mode_locfit modelSelect multipleABC normalise organize.poststat organizeSCRM pairFST pickWindows plot_error plot_errorABC plot_msel plot_param plot_Posteriors plot_stats plot_weighted poolSim poolStats popsFST poststat prepareData prepareFile priorsMatrix regABC rejABC remove_quantileReads remove_realReads removeVar runSCRM scaled.migration scaledPrior shared sim_modelSel simulationABC singleABC statsContig summary_modelSelect Tmatrix tranf weighted_stats

Dependencies:cli coda codetools colorspace doParallel fansi farver foreach ggplot2 glue gtable isoband iterators labeling lattice lifecycle locfit magrittr MASS Matrix MatrixModels mcmc MCMCpack Metrics MetricsWeighted mgcv munsell nlme nnet pillar pkgconfig poolHelper quantreg R6 RColorBrewer Rcpp rlang scales scrm SparseM survival tibble utf8 vctrs viridisLite withr

poolABC

Rendered frompoolABC.Rmdusingknitr::rmarkdownon Oct 27 2024.

Last update: 2023-08-09
Started: 2023-07-06

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Parameter estimation with Approximate Bayesian Computation with several targets	ABC
Import and clean a single file containing data in 'popoolation2' format	cleanData
Create SCRM command line for a model with two populations	cmd2pops
Create SCRM command line for a parallel origin scenario	cmdParallel
Create SCRM command line for a single origin scenario	cmdSingle
Create a header for a _rc file of popoolation2	createHeader
Draw parameters from the priors	createParams
Compute error in model selection with Approximate Bayesian Computation	error_modelSel
Force the simulations to contain the required number of loci	forceLocus
Calculate the mode of a distribution	getmode
Import multiple files containing data in PoPoolation2 format	importContigs
Parameter estimation with Approximate Bayesian Computation using rejection sampling and recording just the index of accepted simulations	index.rejABC
Matrix of prior limits	limits
Merge posterior distributions	mergepost
Compute mode of a locfit object	mode_locfit
Perform model selection with Approximate Bayesian Computation	modelSelect
Parameter estimation with Approximate Bayesian Computation for multiple targets	multipleABC
Matrix of simulated parameter values	myparams
Matrix of simulated parameter values	params
Prediction error plots for ABC using a list	plot_errorABC
Plot model misclassification	plot_msel
Plot the density estimation of a given parameter	plot_param
Plot multiple posterior distributions	plot_Posteriors
Plot the fit of a summary statistic to the target	plot_stats
Plot the density estimation of a given parameter	plot_weighted
Simulation of Pooled DNA sequencing	poolSim
Compute summary statistics from Pooled DNA sequencing	poolStats
Calculate point estimates from the posterior distribution	poststat
Organize information by contig - for multiple data files	prepareData
Organize information by contigs - for a single data file	prepareFile
Construct matrix of prior limits	priorsMatrix
Data frame with an example of observed data	rc1
Data frame with an example of observed data	rc2
Parameter estimation with Approximate Bayesian Computation using local linear regression	regABC
Parameter estimation with Approximate Bayesian Computation using rejection sampling	rejABC
Remove sites using quantiles of the depth of coverage	remove_quantileReads
Remove sites, according to their coverage, from real data	remove_realReads
Run scrm and obtain genotypes	runSCRM
Compute scaled migration rates	scaled.migration
Compute scaled migration rate limits	scaledPrior
Leave-one-out cross validation of model selection	sim_modelSel
Perform an Approximate Bayesian Computation simulation study	simulationABC
Parameter estimation with Approximate Bayesian Computation for a single target	singleABC
Posterior model probabilities	summary_modelSelect
Matrix of summary statistics computed from simulated data	sumstats