# Approximate Bayesian Computation with Pooled Sequencing Data

## Documentation for package ‘poolABC’ version 1.0.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

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