Structurama: Bayesian inference of population structure

John P. Huelsenbeck, Peter Andolfatto, Edna T. Huelsenbeck

Research output: Contribution to journalArticle

79 Scopus citations

Abstract

Structurama is a program for inferring population structure. Specifically, the program calculates the posterior probability of assigning individuals to different populations. The program takes as input a file containing the allelic information at some number of loci sampled from a collection of individuals. After reading a data file into computer memory, Structurama uses a ibbs algorithm to sample assignments of individuals to populations. The program implements four different models: The number of populations can be considered fixed or a random variable with a Dirichlet process prior; moreover, the genotypes of the individuals in the analysis can be considered to come from a single population (no admixture) or as coming from several different populations (admixture). The output is a file of partitions of individuals to populations that were sampled by the Markov chain Monte Carlo algorithm. The partitions are sampled in proportion to their posterior probabilities. The program implements a number of ways to summarize the ampled partitions, including calculation of the 'mean' partition-a partition of the individuals to populations that minimizes the squared distance to the sampled partitions.

Original languageEnglish (US)
Pages (from-to)55-59
Number of pages5
JournalEvolutionary Bioinformatics
Volume2011
Issue number7
DOIs
StatePublished - 2011

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Computer Science Applications

Keywords

  • Bayesian estimaion
  • Dirichlet process prior
  • Markov chain monte carlo
  • Population structure
  • References

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    Huelsenbeck, J. P., Andolfatto, P., & Huelsenbeck, E. T. (2011). Structurama: Bayesian inference of population structure. Evolutionary Bioinformatics, 2011(7), 55-59. https://doi.org/10.4137/EBO.S6761