bioRxivBioinformaticsPreprint
PathogenSurveillance: an automated pipeline for population genomic analyses and pathogen identification
Zachary FosteriD, Martha A. SudermanniD, Camilo H. Parada-RojasiD, Logan K. BlairiD, Fernanda Iruegas-BocardoiD, Upasana DhakaliD, Ricardo Iván Alcalá-BriseñoiD, Hung Phan, Tori R. SchummeriD, Alexandra J. WeisbergiD, Jeff H. ChangiD, Niklaus J. GrünwaldiD
Abstract
Whole genome sequencing (WGS) offers a comprehensive, organism-agnostic method that effectively meets the need for efficient, reliable, and standardized responses to emerging threats from pathogens and pests. Here, we present PathogenSurveillance, an open-source and automated Nextflow pipeline for population genomic analyses of WGS data. It is designed with features tailored for biosurveillance and is suitable for in-field or point-of-care diagnostics. PathogenSurveillance is flexible, accommodating short- and long-read datasets and mixed samples of prokaryotes and/or eukaryotes. It automates all steps, including reference identification and retrieval from the NCBI Assembly database, and produces customizable interactive reports with summaries, phylogenetic trees, and minimum spanning networks that enable species and subspecies level identification. It also outputs quality control metrics and carefully names and organizes output files to facilitate downstream analyses. The pipeline runs on any Linux-based system and minimizes the need for advanced computational expertise. Source code is available on GitHub under the open-source MIT license. The pipeline expands the toolkit for real-time biosurveillance, enabling rapid detection and monitoring of pathogens and pests for rapid response to novel variants.
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: benchmarking
- research focus: software / tool
- approach: experimental assay
- Citations
- 3
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