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jaatha (version 2.6)

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

276

Version

2.6

License

GPL (>= 3)

Maintainer

Paul R Staab

Last Published

September 3rd, 2014

Functions in jaatha (2.6)

Jaatha.getLikelihoods

Gives the best estimates after a Jaatha search

Calculates the JSFS for data imported with ape

Jaatha.refinedSearch

Iterative search for the maximum composite likelihood parameters

Jaatha.getCIsFromLogs

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

Function to perform simulation using ms

Fast estimation of demographic parameters

dm.createDemographicModel

Create a basic demographic model

dm.getLociNumber

Gets how many loci belong to a group of loci

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

Adds an outgroup to a demographic model

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

dm.createThetaTauModel

Creates a standard "Theta/Tau" demopraphic model.

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

Simulates data according to a demographic model

dm.setLociNumber

Defines how many identical loci belong to a group of loci

dm.addSummaryStatistic

Adds a summary statistic to the model.

Jaatha.setSeqgenExecutable

Set the path to the executable for seqgen

dm.addMutationRateHeterogenity

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

Adds mutations to a demographic model

dm.setMutationModel

Defines what mutation model is used for simulations

Jaatha.getStartingPoints

Print Start points

dm.setLociLength

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

convertSimResultsToDataFrame

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

dm.addMigration

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

simulateWithinBlock

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

dm.getLociLength

Gets how long the loci in a group are

dm.addParameter

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

dm.addRecombination

Adds recombination events to a demographic model

Jaatha.confidenceIntervals

Function for calculating bootstrap confidence intervals for jaatha estimates.

fitGlmPoiTransformed

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

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

dm.addSymmetricMigration

Adds symmetric migration between all populations

Fits a Generalized Linear Model within a block.

findBestParInBlock

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

dm.addSampleSize

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

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

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

Returns the groups currently in the model

The function that actually executes the simulations from within Jaatha.

estimateLogLikelihood

Estimates the likelihood for a parameter combination

Jaatha.initialize

Initialization of a Jaatha estimation for population genetics

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

Jaatha.initialSearch

Search the parameter space for good starting positions

dm.addSpeciationEvent

Adds a speciation event to a demographic model

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

dm.addSizeChange

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