Evidence map›Paper›PMID 41306380›Full record

ArticleBioinformatics advances2025

MutSeqR: an open source R package for standardized analysis of error-corrected next-generation sequencing data in genetic toxicology.

Annette E Dodge, Andrew Williams, Danielle P M LeBlanc, David M Schuster, Elena Esina, Charles C Valentine, Jesse J Salk, Alex Y Maslov, Chris Bradley, Carole L Yauk and 2 more

Abstract read
In one paragraph

Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

12 authors.

Annette E DodgeEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada.ORCID https://orcid.org/0000-0002-0446-9055
Andrew WilliamsEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada.
Danielle P M LeBlancEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada.ORCID https://orcid.org/0000-0002-3847-8371
David M SchusterDepartment of Biology, University of Ottawa, Ottawa, ON K1N 6N5, Canada.ORCID https://orcid.org/0009-0001-6316-4358
Elena EsinaDepartment of Biology, University of Ottawa, Ottawa, ON K1N 6N5, Canada.
Charles C ValentineFulcrum Genomics LLC, Somerville, MA 02144, United States.ORCID https://orcid.org/0000-0001-5630-7368
Jesse J SalkDivision of Hematology and Oncology, University of Washington School of Medicine, Seattle, WA 98195, United States.ORCID https://orcid.org/0000-0002-7804-0550
Alex Y MaslovDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, United States.
Chris BradleyMatter Bioworks, Brooklyn, NY 11237, United States.
Carole L YaukDepartment of Biology, University of Ottawa, Ottawa, ON K1N 6N5, Canada.ORCID https://orcid.org/0000-0002-6725-3454
Francesco MarchettiEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada.ORCID https://orcid.org/0000-0002-9435-4867
Matthew J MeierEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada.ORCID https://orcid.org/0000-0001-8199-8754

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Error-corrected next-generation sequencing (ECS) methods are increasingly used to assess mutagenicity and other genetic toxicology endpoints. The lack of open and standardized bioinformatic workflows and tools poses challenges to data reproducibility, comparability, and consistency in interpretation for its application in genetic toxicity assessment. Results: We present MutSeqR, an open source R package to analyse ECS mutation data for genetic toxicology studies. MutSeqR offers practical variant filtering, comparative analysis of mutation frequency between experimental conditions, dose-response assessment via benchmark dose calculations, mutation spectrum analysis, and clonality analyses. We demonstrate MutSeqR's application using published datasets on mice treated with benzo[a]pyrene or benzo[b]fluoranthene, analysed using Duplex Sequencing and SMM-seq, respectively. MutSeqR's flexible functions enable reproducible analyses across ECS platforms, facilitating research and regulatory applications in mutagenicity testing. Availability and implementation: MutSeqR is freely available under an open source license at https://github.com/EHSRB-BSRSE-Bioinformatics/MutSeqR. Implemented in R (version 3.4.0 or greater), it supports all major operating systems. Sequencing data for Project 1 has been deposited in the Sequence Read Archive under accession number PRJNA803048. Variant call files for Project 2 are available on Mendeley Data (doi: 10.17632/65dnysxym8.1).

Identifiers

PMID41306380
PMCPMC12645840

What Socratic holds

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LicenceCC BY
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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 Socratic graph.