Evidence map›Paper›PMID 39487150›Full record

ArticleNature communications2024

A comprehensive comparison of tools for fitting mutational signatures.

Matúš Medo, Charlotte K Y Ng, Michaela Medová

Abstract readComparative Study
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Mutational signatures in hematological malignancies.Einstein (Sao Paulo, Brazil) · 2026
    Review
  9. Review
  10. Article
  11. Article
  12. Article
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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.

Matúš MedoDepartment of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland. matus.medo@unibe.ch.ORCID 0000-0001-8865-9085
Charlotte K Y NgDepartment for BioMedical Research, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0002-6100-0026
Michaela MedováDepartment of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0003-0649-469X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mutational signatures connect characteristic mutational patterns in the genome with biological or chemical processes that take place in cancers. Analysis of mutational signatures can help elucidate tumor evolution, prognosis, and therapeutic strategies. Although tools for extracting mutational signatures de novo have been extensively benchmarked, a similar effort is lacking for tools that fit known mutational signatures to a given catalog of mutations. We fill this gap by comprehensively evaluating twelve signature fitting tools on synthetic mutational catalogs with empirically driven signature weights corresponding to eight cancer types. On average, SigProfilerSingleSample and SigProfilerAssignment/MuSiCal perform best for small and large numbers of mutations per sample, respectively. We further show that ad hoc constraining the list of reference signatures is likely to produce inferior results. Evaluation of real mutational catalogs suggests that the activity of signatures that are absent in the reference catalog poses considerable problems to all evaluated tools.

Indexed as

MutationNeoplasmsAlgorithmsComputational BiologyDNA Mutational AnalysisHumansSoftware

Identifiers

PMID39487150
PMCPMC11530434

What OpenQuestion 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 OpenQuestion graph.