PGIP: A web server for the rapid taxonomic identification of parasite genomes

Background: Parasitic diseases remain a global health challenge, and traditional methods in their diagnosis face limitations in sensitivity and scalability. Genome-based sequencing technologies have improved and are increasingly employed for the identification of parasites; however, their clinical adoption remains hindered by the complexity of bioinformatics analysis, reliance on incomplete reference databases, and accessibility barriers for non-specialists. Overcoming these challenges necessitates the development of standardized analytical workflows and high-quality genomic resources specifically tailored for parasite identification. Methods: We developed a user-friendly web server named the Parasite Genome Identification Platform (PGIP). The reference database was sourced from NCBI, WormBase, and ENA, rigorously filtered for quality, and deduplicated using CD-HIT to ensure accuracy and non-redundancy. To streamline analysis, we integrated a standardized identification pipeline built on Nextflow, which encompasses host DNA depletion, quality control, parasite species identification via both reads mapping and assembly-based approaches, and automated report generation for comprehensive diagnostic insights. Results: PGIP integrates a curated database of 280 parasite genomes; which is rigorously filtered for quality and taxonomic accuracy. Validation across diverse datasets demonstrated the precise species-level resolution of PGIP, and its compatibility with clinical samples. The platform features an intuitive graphic interface;​ and one-click analysis significantly reduces reliance on bioinformatics expertise, thus enabling rapid diagnosis. Conclusions: PGIP offers an accurate, efficient, and a user-friendly web server designed to simplify and accelerate the taxonomic identification of parasite genomes using data from metagenomic next-generation sequencing. Its automated framework reduces the need for specialized expertise, enabling rapid application in clinical and public health settings.