Castanet: a pipeline for rapid analysis of targeted multi-pathogen genomic data

• DOI: 10.1093/bioinformatics/btae591
• Publication Date: 2024-10-03T14:23:27Z
• Authors: Richard Mayne; Shannah Secret; Cyndi Geoghegan; Amy Trebes; Kai Kean; Kaitlin Reid; Gu-Lung Lin; M Azim Ansari; Mariateresa de Ce...; David Bonsall; Ivo Elliott; Paolo Piazza; Anthony Brown; James Bray; Julian C Knight; Heli Harvala; Judith Breuer; Peter Simmonds; Rory J Bowden; Tanya Golubchik

Abstract Motivation Target enrichment strategies generate genomic data from multiple pathogens in a single process, greatly improving sensitivity over metagenomic sequencing and enabling cost-effective, high throughput surveillance clinical applications. However, uptake by research laboratories is constrained an absence of computational tools that are specifically designed for the analysis multi-pathogen sequence data. Here we present pipeline, Castanet, use with Castanet to work short-read produced existing targeted strategies, but can be readily deployed on any BAM file generated another methodology. Also included optional graphical interface installer script. Results In addition genome reconstruction, reports method-specific metrics enable quantification capture efficiency, estimation pathogen load, differentiation low-level positives contamination, assessment quality. used as traditional end-to-end pipeline consensus generation, its strength lies ability process flexible, pre-defined set interest directly experiments. our tests, sequences were accurate reconstructions reference sequences, including instances where strains same present. performs effectively standard computers entire output 96-sample run (50M reads) using batch command, $<$2 h. Availability Implementation Source code freely available under GPL-3 license at https://github.com/MultipathogenGenomics/castanet, implemented Python 3.10 supported Ubuntu Linux 22.04. Supplementary Information journal’s web site. Supporting https://www.ebi.ac.uk/ena/browser/view/PRJEB77004.