Evidence map›Paper›PMID 42271624›Full record

ArticleBioinformatics (Oxford, England)2026

LCR-modules: a collection of workflows for cancer genome analysis.

Kostiantyn Dreval, Laura K Hilton, Bruno M Grande, Giuliano Banco, Krysta M Coyle, Manuela Cruz, Sierra Gillis, Luke Klossok, Prasath Pararajalingam, Christopher K Rushton and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

18 authors.

Kostiantyn DrevalDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Laura K HiltonCentre for Lymphoid Cancer, BC Cancer Research Institute, Vancouver, BC, V5Z 1L3, Canada.
Bruno M GrandeDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Giuliano BancoDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Krysta M CoyleDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Manuela CruzDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Sierra GillisBasic and Translational Research, BC Cancer Research Institute, Vancouver, BC, V5Z 1L3, Canada.
Luke KlossokDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Prasath PararajalingamDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Christopher K RushtonDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Haya ShaalanDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Nicole ThomasDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Helena WinataDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Jasper WongCentre for Lymphoid Cancer, BC Cancer Research Institute, Vancouver, BC, V5Z 1L3, Canada.
Jacky YiuDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Christian SteidlCentre for Lymphoid Cancer, BC Cancer Research Institute, Vancouver, BC, V5Z 1L3, Canada.
David W ScottCentre for Lymphoid Cancer, BC Cancer Research Institute, Vancouver, BC, V5Z 1L3, Canada.
Ryan D MorinDepartment of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.ORCID 0000-0003-2932-7800

Funding

Terry Fox New Investigator 1043
6 · The paper itself

Abstract

motivationThe surge of genomic data from advanced sequencing technologies is outpacing current analytical pipelines. We introduce LCR-modules, an open-source suite of bioinformatics tools designed for flexible and automated cancer genome data analysis. LCR-modules enables reproducible analysis of diverse cancer genomics data at scale. The suite comprises 49 Snakemake-based workflows organized into three levels, facilitating tasks from low-level quality control to complex cohort-level analyses. LCR-modules supports various sequencing types and integrates pipelines such as mutation calling, expression quantification, and cohort-level aggregation, ensuring flexibility and reproducibility. LCR-modules represents a significant advancement in genomic data analysis, reducing barriers in reproducibility and scalability and has already been applied to a combination of exomes and genomes from over 10 800 samples. AVAILABILITY: No new data were generated in support of this research. The source code for the LCR-modules is openly available at https://github.com/LCR-BCCRC/lcr-modules.

Indexed as

Computational BiologyGenomicsNeoplasmsSoftwareHumansWorkflow

Identifiers

PMID42271624
PMCPMC13284989

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.