Kostiantyn Dreval, Laura K. Hilton, Bruno M. Grande, Giuliano Banco, Krysta M. Coyle, Manuela Cruz, Sierra Gillis, Luke Klossok, Prasath Pararajalingam, Christopher Rushton, Haya Shaalan, Nicole Thomas, Helena Winata, Jasper Wong, Jacky Yiu, Christian Steidl, David W. Scott, Ryan D. Morin
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.