Evidence map›Paper›PMID 30271907›Full record

ArticleCommunications biology2018

Genome-wide somatic variant calling using localized colored de Bruijn graphs.

Giuseppe Narzisi, André Corvelo, Kanika Arora, Ewa A Bergmann, Minita Shah, Rajeeva Musunuri, Anne-Katrin Emde, Nicolas Robine, Vladimir Vacic, Michael C Zody

Abstract read
In one paragraph

Article in Communications biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers.

0numbers the graph read from it
0cells of the map it votes in
95citing 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

95 citing papers in PubMed.

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  11. A Single-Cell Atlas of Uterine Carcinosarcoma from Diverse Ancestries.bioRxiv : the preprint server for biology · 2026
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  20. The Open Pediatric Cancer Project.bioRxiv : the preprint server for biology · 2025
    Article

35 more citing papers are in PubMed but not listed here.

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

10 authors.

Giuseppe NarzisiNew York Genome Center, New York, NY, 10013, USA. gnarzisi@nygenome.org.ORCID http://orcid.org/0000-0003-1118-8849
André CorveloNew York Genome Center, New York, NY, 10013, USA.
Kanika AroraNew York Genome Center, New York, NY, 10013, USA.
Ewa A BergmannNew York Genome Center, New York, NY, 10013, USA.
Minita ShahNew York Genome Center, New York, NY, 10013, USA.
Rajeeva MusunuriNew York Genome Center, New York, NY, 10013, USA.
Anne-Katrin EmdeNew York Genome Center, New York, NY, 10013, USA.
Nicolas RobineNew York Genome Center, New York, NY, 10013, USA.
Vladimir VacicNew York Genome Center, New York, NY, 10013, USA.ORCID http://orcid.org/0000-0001-6571-2293
Michael C ZodyNew York Genome Center, New York, NY, 10013, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reliable detection of somatic variations is of critical importance in cancer research. Here we present Lancet, an accurate and sensitive somatic variant caller, which detects SNVs and indels by jointly analyzing reads from tumor and matched normal samples using colored de Bruijn graphs. We demonstrate, through extensive experimental comparison on synthetic and real whole-genome sequencing datasets, that Lancet has better accuracy, especially for indel detection, than widely used somatic callers, such as MuTect, MuTect2, LoFreq, Strelka, and Strelka2. Lancet features a reliable variant scoring system, which is essential for variant prioritization, and detects low-frequency mutations without sacrificing the sensitivity to call longer insertions and deletions empowered by the local-assembly engine. In addition to genome-wide analysis, Lancet allows inspection of somatic variants in graph space, which augments the traditional read alignment visualization to help confirm a variant of interest. Lancet is available as an open-source program at https://github.com/nygenome/lancet.

Identifiers

PMID30271907
PMCPMC6123722

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.