Evidence map›Paper›PMID 40964253›Full record

ArticlebioRxiv : the preprint server for biology2025

kSanity: A k-mer based application for precision bacterial strain detection and quantification.

Michael France, Issac Chaudry, Joseph Elsherbini, Jacques Ravel

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

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

4 authors.

Michael FranceCenter for Advanced Microbiome Research and Innovation, Institute for Genome Sciences, University of Maryland, School of Medicine, Maryland, USA.ORCID 0000-0002-6029-0201
Issac ChaudryCenter for Advanced Microbiome Research and Innovation, Institute for Genome Sciences, University of Maryland, School of Medicine, Maryland, USA.ORCID 0000-0002-3497-3105
Joseph ElsherbiniRagon Institute of Mass General, MIT, and Harvard, Massachusetts, USA.
Jacques RavelCenter for Advanced Microbiome Research and Innovation, Institute for Genome Sciences, University of Maryland, School of Medicine, Maryland, USA.ORCID 0000-0002-0851-2233

Funding

Systems-Level Research in Microbial PathogenesisT32AI162579 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI NICHOLAS H CARBONETTI, Julie Dunning Hotopp · 2022 to 2026
$1.7M
NIAID NIH HHS T32 AI162579
6 · The paper itself

Abstract

Motivation: Accurate detection and quantification of bacterial strains in clinical samples is necessary to measure their colonization and persistence. Past methods to achieve this relied either on strain-specific qPCR assays, or shotgun metagenomic read mapping approaches. The resident microbial community is a major source of interference in both assays because it can contain conspecific strains bearing similarity to the focal strain(s). Results: We present kSanity, a k-mer based application for the detection and quantification of targeted bacterial strains in shotgun metagenomic data. Because kSanity uses exact string matches between the reads and reference, it is less sensitive to interference by conspecific strains. We test the performance of kSanity using a combination of Availability and implementation: kSanity is available at: https://github.com/ravel-lab/kSanity.

Indexed as

bacterial strain detectionmetagenomics

Identifiers

PMID40964253
PMCPMC12439994

What OpenQuestion holds

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LicenceCC BY
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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.