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Nucleic Acids Res. 2019 Jun 20;47(11):5539-5549. doi: 10.1093/nar/gkz361.

Fast hierarchical Bayesian analysis of population structure.

Author information

1
Parasites and Microbes, Wellcome Sanger Institute, Cambridge, CB10 1SA, UK.
2
Department of Microbiology, New York University School of Medicine, NY 10016, USA.
3
Department of Veterinary Medicine, University of Cambridge, Cambridge, CB3 0ES, UK.
4
The Alan Turing Institute, London, NW1 2DB, UK.
5
Department of Biostatistics, University of Oslo, Blindern 0317, Norway.
6
Helsinki Institute for Information Technology HIIT, Department of Mathematics and Statistics, University of Helsinki, Aalto FI-00076, Finland.

Abstract

We present fastbaps, a fast solution to the genetic clustering problem. Fastbaps rapidly identifies an approximate fit to a Dirichlet process mixture model (DPM) for clustering multilocus genotype data. Our efficient model-based clustering approach is able to cluster datasets 10-100 times larger than the existing model-based methods, which we demonstrate by analyzing an alignment of over 110 000 sequences of HIV-1 pol genes. We also provide a method for rapidly partitioning an existing hierarchy in order to maximize the DPM model marginal likelihood, allowing us to split phylogenetic trees into clades and subclades using a population genomic model. Extensive tests on simulated data as well as a diverse set of real bacterial and viral datasets show that fastbaps provides comparable or improved solutions to previous model-based methods, while being significantly faster. The method is made freely available under an open source MIT licence as an easy to use R package at https://github.com/gtonkinhill/fastbaps.

PMID:
31076776
PMCID:
PMC6582336
DOI:
10.1093/nar/gkz361
[Indexed for MEDLINE]
Free PMC Article

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