Evidence map›Paper›PMID 30486787›Full record

ArticleBMC genomics2018

Helmsman: fast and efficient mutation signature analysis for massive sequencing datasets.

Jedidiah Carlson, Jun Z Li, Sebastian Zöllner

Abstract read
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
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  4. Diffsig: Associating Risk Factors with Mutational Signatures.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024
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  7. Review
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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

3 authors.

Jedidiah CarlsonDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA. jedidiah@umich.edu.ORCID http://orcid.org/0000-0002-1363-872X
Jun Z LiDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Sebastian ZöllnerDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.

Funding

University of Michigan Training Program in Genomic ScienceT32HG000040 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sebastian Zoellner · 1995 to 2026
$16.4M
High-resolution map of human germline mutation patterns and inference of mutagenic mechanismsR01GM118928 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LI, JUN, ZOELLNER, SEBASTIAN · 2016 to 2019
$1.2M
NHGRI NIH HHS T32 HG000040NIGMS NIH HHS R01 GM118928NIH HHS R01GM118928
6 · The paper itself

Abstract

backgroundThe spectrum of somatic single-nucleotide variants in cancer genomes often reflects the signatures of multiple distinct mutational processes, which can provide clinically actionable insights into cancer etiology. Existing software tools for identifying and evaluating these mutational signatures do not scale to analyze large datasets containing thousands of individuals or millions of variants.

resultsWe introduce Helmsman, a program designed to perform mutation signature analysis on arbitrarily large sequencing datasets. Helmsman is up to 300 times faster than existing software. Helmsman's memory usage is independent of the number of variants, resulting in a small enough memory footprint to analyze datasets that would otherwise exceed the memory limitations of other programs.

conclusionsHelmsman is a computationally efficient tool that enables users to evaluate mutational signatures in massive sequencing datasets that are otherwise intractable with existing software. Helmsman is freely available at https://github.com/carjed/helmsman .

Indexed as

SoftwareDNA Mutational AnalysisHigh-Throughput Nucleotide SequencingMutationReproducibility of ResultsCancer genomicsMutational signaturesPythonSingle nucleotide variants

Identifiers

PMID30486787
PMCPMC6263557

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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 OpenQuestion graph.