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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·Haya Shaalan·Nicole Thomas·Helena Winata·Jasper Wong·Jacky Yiu·Christian Steidl·David W Scott·Ryan D Morin
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Abstract

MOTIVATION: The 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.

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Kostiantyn Dreval, Laura K Hilton, Bruno M Grande, Giuliano Banco, Krysta M Coyle, Manuela Cruz, Sierra Gillis, Luke Klossok, Prasath Pararajalingam, Christopher K Rushton, Haya Shaalan, Nicole Thomas, Helena Winata, Jasper Wong, Jacky Yiu, Christian Steidl, David W Scott, Ryan D Morin. 2026-06-01. LCR-modules: a collection of workflows for cancer genome analysis.. https://doi.org/10.1093/bioinformatics%2Fbtag366

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