SAMURAI: shallow analysis of copy number alterations using a reproducible and integrated bioinformatics pipeline
Year: 2024
Type: article
Abstract: Shallow whole-genome sequencing (sWGS) offers a cost-effective approach to detect copy number alterations (CNAs). However, there remains a gap for a standardized workflow specifically designed for sWGS analysis. To address this need, in this work we present SAMURAI, a bioinformatics pipeline specifically designed for analyzing CNAs from sWGS data in a standardized and reproducible manner. SAMURAI is built using established community standards, ensuring portability, scalability, and reproducibility. The pipeline features a modular design with independent blocks for data preprocessing, copy number analysis, and customized reporting. Users can select workflows tailored for either solid or liquid biopsy analysis (e.g. circulating tumor DNA), with specific tools integrated for each sample type. The final report generated by SAMURAI provides detailed results to facilitate data interpretation and potential downstream analyses. To demonstrate its robustness, SAMURAI was validated using simulated and real-world data sets. The pipeline achieved high concordance with ground truth data and maintained consistent performance across various scenarios. By promoting standardization and offering a versatile workflow, SAMURAI empowers researchers in diverse environments to reliably analyze CNAs from sWGS data. This, in turn, holds promise for advancements in precision medicine.
Source: Briefings in Bioinformatics
DOI: 10.1093/bib/bbaf035
Authors: Sara Potente, Diego Boscarino, Dino Paladin, Sergio Marchini, Luca Beltrame, Chiara Romualdi
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,922
OpenAlex ID: W4406932472