ArticleGenome research2023
Genealogical inference and more flexible sequence clustering using iterative-PopPUNK.
Article in Genome research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Efficacy and safety of tumor necrosis factor-α inhibitors and mesenchymal stem cells in the treatment of fistulizing Crohn's disease: a systematic review and network meta-analysis.Frontiers in immunology · 2026Pooled it
- A reusable model of pangenome selection informs optimal surveillance strategies over vaccine introductions.Genome medicine · 2026Article
- Imported, not invented, genes prevail amongProceedings of the National Academy of Sciences of the United States of America · 2026Article
- A bacterial ecocline in Klebsiella pneumoniae may explain its backboned phylogeny.PLoS biology · 2026Article
- Propensity for proto-gene emergence in bacteria.Genome biology · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
Bacterial genome data are accumulating at an unprecedented speed due to the routine use of sequencing in clinical diagnoses, public health surveillance, and population genetics studies. Genealogical reconstruction is fundamental to many of these uses; however, inferring genealogy from large-scale genome data sets quickly, accurately, and flexibly is still a challenge. Here, we extend an alignment- and annotation-free method, PopPUNK, to increase its flexibility and interpretability across data sets. Our method, iterative-PopPUNK, rapidly produces multiple consistent cluster assignments across a range of sequence identities. By constructing a partially resolved genealogical tree with respect to these clusters, users can select a resolution most appropriate for their needs. We showed the accuracy of clusters at all levels of similarity and genealogical inference of iterative-PopPUNK based on simulated data and obtained phylogenetically concordant results in real data sets from seven bacterial species. Using two example sets of
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Registered trials
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