Parapipe: a pipeline for parasite next-generation sequencing data analysis applied to Cryptosporidium

<i>Cryptosporidium</i>, a protozoan parasite of significant public health concern, is responsible for severe diarrhoeal disease, particularly in immunocompromised individuals and young children in resource-limited settings. Analysis of whole-genome next-generation sequencing (NGS) data is critical in improving our understanding of <i>Cryptosporidium</i> epidemiology, transmission and diversity. However, effective analysis of NGS data in a public health context necessitates the development of robust, validated computational tools. We present Parapipe, an ISO-accreditable bioinformatic pipeline for high-throughput analysis of NGS data from <i>Cryptosporidium</i> and related taxa. Built using Nextflow DSL2 and containerized with Singularity, Parapipe is modular, portable, scalable and designed for use by public health laboratories. Using both simulated and real <i>Cryptosporidium</i> datasets, we demonstrate the power of Parapipe's genomic analysis for generating epidemiological insights. We highlight how whole-genome analysis yields substantially greater phylogenetic resolution than conventional <i>gp60</i> molecular typing in <i>Cryptosporidium parvum</i>. Uniquely, Parapipe facilitates the integration of mixed infection analysis and phylogenomic clustering with epidemiological metadata, representing a powerful tool in the investigation of complex transmission pathways and identification of outbreak sources. Parapipe significantly advances genomic surveillance of <i>Cryptosporidium</i>, offering a streamlined, reproducible analytical framework. By automating a complex workflow and delivering detailed genomic characterization, Parapipe provides a valuable tool for public health agencies and researchers, supporting efforts to mitigate the global burden of cryptosporidiosis.