Evidence map›Paper›PMID 40205174›Full record

ArticleNature methods2025

Efficient and robust search of microbial genomes via phylogenetic compression.

Karel Břinda, Leandro Lima, Simone Pignotti, Natalia Quinones-Olvera, Kamil Salikhov, Rayan Chikhi, Gregory Kucherov, Zamin Iqbal, Michael Baym

Abstract read
In one paragraph

Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. BWT construction and search at the terabase scale.Bioinformatics (Oxford, England) · 2024
    Article
  14. Article
  15. Where the Patterns Are: Repetition-Aware Compression for Colored de Bruijn GraphsJournal of computational biology : a journal of computational molecular cell biology · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Karel BřindaInria, Irisa, Univ. Rennes, Rennes, France. karel.brinda@inria.fr.ORCID http://orcid.org/0000-0003-0200-557X
Leandro LimaEMBL-EBI, Hinxton, UK.
Simone PignottiDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0009-0003-3660-6960
Natalia Quinones-OlveraDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0002-4612-6819
Kamil SalikhovLIGM, CNRS, Univ. Gustave Eiffel, Marne-la-Vallée, France.
Rayan ChikhiInstitut Pasteur, Univ. Paris Cité, G5 Sequence Bioinformatics, Paris, France.ORCID http://orcid.org/0000-0003-1099-8735
Gregory KucherovLIGM, CNRS, Univ. Gustave Eiffel, Marne-la-Vallée, France.ORCID http://orcid.org/0000-0001-5899-5424
Zamin IqbalEMBL-EBI, Hinxton, UK.ORCID http://orcid.org/0000-0001-8466-7547
Michael BaymDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. baym@hms.harvard.edu.ORCID http://orcid.org/0000-0003-1303-5598

Funding

Evolutionary Tradeoffs in Antibiotic ResistanceR35GM133700 · NIGMS · HARVARD MEDICAL SCHOOL · PI BAYM, MICHAEL · 2019 to 2023
$2.4M
NIGMS NIH HHS R35 GM133700
6 · The paper itself

Abstract

Comprehensive collections approaching millions of sequenced genomes have become central information sources in the life sciences. However, the rapid growth of these collections has made it effectively impossible to search these data using tools such as the Basic Local Alignment Search Tool (BLAST) and its successors. Here, we present a technique called phylogenetic compression, which uses evolutionary history to guide compression and efficiently search large collections of microbial genomes using existing algorithms and data structures. We show that, when applied to modern diverse collections approaching millions of genomes, lossless phylogenetic compression improves the compression ratios of assemblies, de Bruijn graphs and k-mer indexes by one to two orders of magnitude. Additionally, we develop a pipeline for a BLAST-like search over these phylogeny-compressed reference data, and demonstrate it can align genes, plasmids or entire sequencing experiments against all sequenced bacteria until 2019 on ordinary desktop computers within a few hours. Phylogenetic compression has broad applications in computational biology and may provide a fundamental design principle for future genomics infrastructure.

Indexed as

BacteriaComputational BiologyData CompressionGenome, BacterialGenome, MicrobialGenomicsPhylogenyAlgorithmsSequence AlignmentSoftware

Identifiers

PMID40205174
PMCPMC13340442

What OpenQuestion holds

Textmetadata
LicenceTDM
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.