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jaatha (version 2.7.0)

A Fast Parameter Estimation Method for Evolutionary Biology

Description

Jaatha is a composite likelihood method for inferring evolutionary parameters using genetic data. Given a model of the evolutionary history of two biological populations as well as SNP data from multiple individuals from each population, it estimates model parameters like the time of separation of both species.

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Version

Install

install.packages('jaatha')

Monthly Downloads

321

Version

2.7.0

License

GPL (>= 3)

Maintainer

Paul Staab

Last Published

November 26th, 2014

Functions in jaatha (2.7.0)

Jaatha.confidenceIntervals

Function for calculating bootstrap confidence intervals for jaatha estimates.

The "Jaatha" S4 class saves the basic parameters for a Jaatha estimation procedure

Jaatha.getCIsFromLogs

Function for calculating bootstrap confidence intervals from logs of a previous run of Jaatha.confidenceIntervals.

Low level function for adding a new feature to a demographic Model

Jaatha.setSeqgenExecutable

Set the path to the executable for seqgen

Jaatha.initialSearch

Search the parameter space for good starting positions

convertSimResultsToDataFrame

Converts simulation results into a data frame that is usable for fitting a glm.

dm.addSummaryStatistic

Adds a summary statistic to the model.

dm.addSizeChange

Adds an instantaneous change of the population size of one population to a model.

dm.setLociNumber

Defines how many identical loci belong to a group of loci

Adds an growth or decline of the population size of one population to a model.

simulateWithinBlock

This function executes simulations for a number of random parameter values inside a block.

dm.createDemographicModel

Create a basic demographic model

dm.setMutationModel

Defines what mutation model is used for simulations

Fits a GLM for a summary statistics of type "poisson.smoothed"

Function to set the number of cores that Jaatha uses for simulations

findBestParInBlock

Functions that uses the fitted GLMs to estimate the parameters that have the highest likelihood.

Jaatha.initialize

Initialization of a Jaatha estimation for population genetics

dm.createThetaTauModel

Creates a standard "Theta/Tau" demopraphic model.

dm.getLociLength

Gets how long the loci in a group are

Adds an outgroup to a demographic model

Calculates the JSFS for data imported with ape

fitGlmPoiTransformed

Fits a GLM for a summary statistics of type "poisson.transformed" and "poisson.independent"

Checks if a variable is of a given type and calls stop() on type mismatch

Convert parameters from Jaatha's internal scale into their natural scale

Fits a Generalized Linear Model within a block.

dm.addParameter

Create a parameter that can be used for one or more features

dm.addSymmetricMigration

Adds symmetric migration between all populations

The function that actually executes the simulations from within Jaatha.

Jaatha.refinedSearch

Iterative search for the maximum composite likelihood parameters

dm.getLociNumber

Gets how many loci belong to a group of loci

Calculate the JSFS from a list of segregating sites statistics

Convert parameters from the natural scale into Jaatha's internal scale

estimateLogLikelihood

Estimates the likelihood for a parameter combination

dm.addMutationRateHeterogenity

Allows the mutation rate on different sites within one locus to vary according to a Gamma Distribution.

dm.addRecombination

Adds recombination events to a demographic model

Fast estimation of demographic parameters

Adds mutations to a demographic model

Jaatha.getStartingPoints

Print Start points

Returns the groups currently in the model

dm.addSpeciationEvent

Adds a speciation event to a demographic model

Jaatha.getLikelihoods

Gives the best estimates after a Jaatha search

dm.addSampleSize

Sets how many individuals from each population are sampled at time 0.

dm.addMigration

Add migration/gene flow between two populations to a demographic model

dm.setLociLength

Defines the sequence length of each loci in a group of loci

Simulates data according to a demographic model