ABC as a flexible framework to estimate demography over space and time: some cons, many pros

  title={ABC as a flexible framework to estimate demography over space and time: some cons, many pros},
  author={Giorgio Bertorelle and Andrea Benazzo and Stefano Mona},
  journal={Molecular Ecology},
The analysis of genetic variation to estimate demographic and historical parameters and to quantitatively compare alternative scenarios recently gained a powerful and flexible approach: the Approximate Bayesian Computation (ABC). The likelihood functions does not need to be theoretically specified, but posterior distributions can be approximated by simulation even assuming very complex population models including both natural and human‐induced processes. Prior information can be easily… 

Inferring past demographic changes from contemporary genetic data: A simulation‐based evaluation of the ABC methods implemented in diyabc

It is concluded that diyabc‐based assessments are not suited to capture a detailed demographic history, but might be efficient at capturing simple, major demographic changes.

Forward-in-Time, Spatially Explicit Modeling Software to Simulate Genetic Lineages Under Selection

It is shown how SELECTOR can be used to investigate genetic differentiation of loci under balancing selection in interconnected demes with spatially heterogeneous gene flow and is efficient and robust for building insight into human settlement history and evolution.

Model choice for phylogeographic inference using a large set of models

This investigation demonstrates that the determination of which models to include in ABC model choice experiments is a vital component of model‐based phylogeographic analysis.

Comparing phylogeographic hypotheses by simulating DNA sequences under a spatially explicit model of coalescence.

A spatially explicit model of coalescence is used to evaluate the potential of several summary statistics to differentiate three typical phylogeographic scenarios and identify conditions in which each summary statistic is useful to infer the evolution of a species range.

Back to BaySICS: A User-Friendly Program for Bayesian Statistical Inference from Coalescent Simulations

The software BaySICS provides an integrated and user-friendly platform that performs ABC analyses by means of coalescent simulations from DNA sequence data and has several capabilities making it a suitable tool for analysing contemporary genetic datasets.

An overview of the utility of population simulation software in molecular ecology

  • S. Hoban
  • Environmental Science
    Molecular ecology
  • 2014
The roles that simulation software can play in molecular ecology studies are explained so that researchers can decide whether, when and precisely how simulations can be incorporated into their work.

Navigating the unknown: model selection in phylogeography

The study by Peter et al. (2010) quantifies the relative fit of competing models for estimating the population genetic parameters of interest and highlights the peril inherent to model‐based inferences that lack a statistical evaluation of the fit of a model to the data.

Detecting Phenotypic Selection by Approximate Bayesian Computation in Phylogenetic Comparative Methods

This chapter discusses the fundamental structure and advantages of the approximate Bayesian computation (ABC) algorithm in phylogenetic comparative methods (PCMs) and analysed trait evolution in which a specific species exhibits an extraordinary trait value relative to others.

Approximate Bayesian Computation in Evolution and Ecology

Although the method arose in population genetics, ABC is increasingly used in other fields, including epidemiology, systems biology, ecology, and agent-based modeling, and many of these applications are briefly described.

A new Approximate Bayesian Computation framework to distinguish among complex evolutionary models using whole-genome data

A new method for inferring demographic history from whole-genome data, ABC-SeS, to analyze the distributions of segregating sites within an Approximate Bayesian Computation framework, using a Random Forest approach is proposed.



ABC: a useful Bayesian tool for the analysis of population data.

  • J. LopesM. Beaumont
  • Computer Science
    Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
  • 2010

Bayesian Estimation of Recent Migration Rates After a Spatial Expansion

The ABC method is used to estimate the expansion time and migration rates for five natural common vole populations in Switzerland typed for a sex-linked marker and a nuclear marker, suggesting that expansion occurred <10,000 years ago, after the most recent glaciation.

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

Key methods used in DIY ABC, a computer program for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples, are described.


The method presented here is the only robust, model‐based method available so far, which allows inferring complex population dynamics over a short time scale and provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

Statistical evaluation of alternative models of human evolution

Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, it is shown that a simple African replacement model with exponential growth has a higher probability as compared with alternative multiregional evolution or assimilation scenarios.

The use of approximate Bayesian computation in conservation genetics and its application in a case study on yellow-eyed penguins

The ABC approach is described and specific parts of its algorithm are identified that are being the subject of intensive studies in order to further expand its usability and discuss applications of this Bayesian algorithm in conservation studies, providing insights on the potentialities of these tools.

Bayesian Analysis of an Admixture Model With Mutations and Arbitrarily Linked Markers

The application of the approximate Bayesian computation (ABC) framework to an artificially admixed domestic bee population from northwest Italy suggests that the admixture occurred in the last 10–40 generations and that the parental Apis mellifera and A. ligustica populations were completely separated since the last glacial maximum.

Fregene: Simulation of realistic sequence-level data in populations and ascertained samples

Main functionalities of both FREGENE and SAMPLE, a companion program that can replicate association study datasets, are described, which will be valuable for assessing the validity of models for selection, demography and population genetic parameters, as well as the efficacy of association studies.

In defence of model‐based inference in phylogeography

It is argued that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics, and is encouraging researchers to study and use model‐based inference in population Genetics.

A statistical evaluation of models for the initial settlement of the american continent emphasizes the importance of gene flow with Asia.

It is estimated that this colonization involved about 100 individuals and occurred some 13,000 years ago, in agreement with well-established archeological data, and that a single, discrete, wave of colonization is highly inconsistent with observed levels of genetic diversity.