Evidence map›Paper›PMID 42065967›Full record

ArticleSTAR protocols2026

Classifying germline and somatic structural variants in tumor-only contexts using GaTSV.

Wolu Chukwu, Siyun Lee, Alexander Crane, Shu Zhang, Jeremiah Wala, Oumayma Dakhama, Gregory Raskind, Julia Sun, Rameen Beroukhim, Frank Dubois and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in STAR protocols, 2026. 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

11 authors.

Wolu ChukwuCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Siyun LeeCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. Electronic address: siyuns_lee@dfci.harvard.edu.
Alexander CraneCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Shu ZhangCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Jeremiah WalaCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Oumayma DakhamaCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Gregory RaskindCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Julia SunCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Rameen BeroukhimCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Frank DuboisCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Institute of Pathology, 10117 Berlin, Germany. Electronic address: frank.dubois@charite.de.
Simona DalinCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. Electronic address: sdalin@broadinstitute.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Distinguishing somatic structural variants (SVs) from germline SVs in the absence of matched normal samples has significant value in elucidating disease-driving processes in cancer. Here, we present a protocol for classifying germline SVs in tumor-only contexts using a support vector machine (SVM)-based algorithm. We describe steps for preparing input data and identifying SVs from whole-genome sequencing (WGS) of tumor samples using the SV caller SvABA. We then detail classification procedures via our germline and tumor structural variant classifier (GaTSV). For complete details on the use and execution of this protocol, please refer to Chukwu et al.

Indexed as

Genomic Structural VariationGerm-Line MutationNeoplasmsComputational BiologyGenomicsHumansSupport Vector MachineWhole Genome SequencingBioinformaticsCancerGenomics

Identifiers

PMID42065967
PMCPMC13141703

What OpenQuestion holds

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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.