Evidence map›Paper›PMID 31076776›Full record

ArticleNucleic acids research2019

Fast hierarchical Bayesian analysis of population structure.

Gerry Tonkin-Hill, John A Lees, Stephen D Bentley, Simon D W Frost, Jukka Corander

Abstract read
In one paragraph

Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 228 papers.

0numbers the graph read from it
0cells of the map it votes in
228citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

228 citing papers in PubMed.

  1. The prevalence and molecular epidemiology ofEmerging microbes & infections · 2026
    Observational
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  4. Emerging trends in invasiveEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2026
    Article
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168 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gerry Tonkin-HillParasites and Microbes, Wellcome Sanger Institute, Cambridge, CB10 1SA, UK.
John A LeesDepartment of Microbiology, New York University School of Medicine, NY 10016, USA.
Stephen D BentleyParasites and Microbes, Wellcome Sanger Institute, Cambridge, CB10 1SA, UK.
Simon D W FrostDepartment of Veterinary Medicine, University of Cambridge, Cambridge, CB3 0ES, UK.
Jukka CoranderParasites and Microbes, Wellcome Sanger Institute, Cambridge, CB10 1SA, UK.

Funding

Timely monitoring and response to HIV transmission networks for intensified preventionR01AI135970 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DENNIS, ANN · 2018 to 2022
$3.8M
Medical Research Council MR/R015600/1NIAID NIH HHS R01 AI135970Wellcome Trust 206194
6 · The paper itself

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.

Indexed as

AlgorithmsBayes TheoremCluster AnalysisDatabases, ProteinModels, TheoreticalBacterial ProteinsComputational BiologyHuman Immunodeficiency Virus ProteinsPhylogenyReproducibility of ResultsBacterial ProteinsHuman Immunodeficiency Virus Proteins

Identifiers

PMID31076776
PMCPMC6582336

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.