Evidence map›Paper›PMID 41279887›Full record

ArticlebioRxiv : the preprint server for biology2025

Seqwin: Ultrafast identification of signature sequences in microbial genomes.

Michael X Wang, Bryce Kille, Michael G Nute, Siyi Zhou, Lauren B Stadler, Todd J Treangen

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Michael X WangDepartment of Computer Science, Rice University, Houston, 77005, USA.ORCID 0000-0001-7009-6958
Bryce KilleDepartment of Computer Science, Rice University, Houston, 77005, USA.ORCID 0000-0003-2946-6915
Michael G NuteDepartment of Computer Science, Rice University, Houston, 77005, USA.ORCID 0000-0003-4129-6525
Siyi ZhouDepartment of Civil and Environmental Engineering, Rice University, Houston, 77005, USA.ORCID 0000-0002-7718-2864
Lauren B StadlerDepartment of Civil and Environmental Engineering, Rice University, Houston, 77005, USA.ORCID 0000-0001-7469-1981
Todd J TreangenDepartment of Computer Science, Rice University, Houston, 77005, USA.ORCID 0000-0002-3760-564X

Funding

TRAINING PROGRAM IN COMPUTATIONAL BIOLOGY AND MEDICINET15LM007093 · NLM · RICE UNIVERSITY · PI Lydia E. Kavraki · 1992 to 2026
$20.8M
Project 3: Functional Microbiome and Host Signatures in Transition from Commensal to pathogenP01AI152999 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ARIAS, CESAR AUGUSTO, SAVIDGE, TOR C. · 2020 to 2025
$12.0M
Identification and enrichment of signature regions of antimicrobial resistant pathogen genomes for wastewater disease surveillanceR21AI190938 · NIAID · RICE UNIVERSITY · PI STADLER, LAUREN · 2025 to 2025
$422k
NIAID NIH HHS P01 AI152999NIAID NIH HHS R21 AI190938NLM NIH HHS T15 LM007093
6 · The paper itself

Abstract

Motivation: Polymerase chain reaction (PCR) enables rapid, cost-effective diagnostics but requires prior identification of genomic regions that allow sensitive and specific identification of target microbial groups, herein referred to as microbial signature sequences. We introduce Seqwin, an open-source framework designed to automate microbial genome signature discovery. Tens of thousands of microbial genomes are now available, limiting the application of existing manual and automated approaches for identifying signatures. Modern approaches that are capable of leveraging all available microbial genomes will ensure sensitive and accurate DNA signatures identification and enable robust pathogen detection for clinical, environmental, and public health applications. Results: Seqwin builds weighted pan-genome minimizer graphs and uses a traversal algorithm to identify signature sequences that occur frequently in target genomes but remain rare in non-targets. Unlike earlier tools that depend on strict presence or absence of sequences, Seqwin accommodates natural sequence variation and scales to very large genome collections. When applied to genomes from Availability: Seqwin is freely available for academic use (https://github.com/treangenlab/Seqwin) and can be installed via Bioconda.

Identifiers

PMID41279887
PMCPMC12637579

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Registered trials

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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.