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Morris, A. V.

Publications and source records attributed to Morris, A. V..

2 recordsLinked to original sources

Parapipe: a Pipeline for Handling Parasite NGS Datasets and its Application to Cryptosporidium

0.0Cryptosporidium, a protozoan parasite of significant public health concern, is responsible for severe diarrheal diseases, particularly in immunocompromised individuals and young children in resource-limited settings. Analysis of whole genome next generation sequencing (NGS) data is a critical next step in improving our understanding of Cryptosporidium epidemiology, transmission dynamics, and genetic diversity. However, effective analysis of NGS data in a public health context necessitates the development of robust, validated bioinformatics tools. Here, we present Parapipe, a modular ISO accreditable bioinformatics pipeline designed for high-throughput processing and analysis of Cryptosporidium NGS datasets. Built using Nextflow DSL2 and containerized with Singularity, Parapipe is portable, scalable, and capable of end-to-end analyses, including quality control, variant calling, multiplicity of infection (MOI) investigations and phylogenomic clustering analysis. Using both simulated and real-world datasets, we demonstrate Parapipes ability to resolve genetic heterogeneity, identify mixed infections, and generate high-resolution phylogenomic insights. Here, we use it to carry out a comparison between whole genome single nucleotide polymorphism (wgSNP) typing and the conventionally used gp60 molecular typing scheme. Compared to existing pipelines, Parapipe uniquely integrates MOI analysis, enabling the differentiation of mixed infections and supporting epidemiological investigations. Parapipes design facilitates integration with geographic, demographic, epidemiological and environmental data, enhancing its utility for tracking transmission pathways and outbreak sources. Parapipe represents a significant advance in utilising genomics for public health surveillance of Cryptosporidium, offering a streamlined and reproducible framework for analysis with potential application to other pathogenic protozoa. By automating complex workflows and enabling detailed genomic characterization, Parapipe provides a valuable tool for public health agencies and researchers, supporting efforts to mitigate the global burden of cryptosporidiosis.

bioinformatics↗

Afanc: a Metagenomics Tool for Variant Level Disambiguation of NGS Datasets

Genomics is amongst the most powerful tools available for mounting a clinical response to infectious disease. The accurate and precise taxonomic evaluation of pathogens is essential when building a picture of pathogenicity, virulence, transmission, and drug resistance. Carrying out such profiling in a high throughput manner necessitates the development of reliable bioinformatic tools. Here we present Afanc, a novel metagenomic profiler which is sensitive down to species and strain level taxa, and capable of elucidating the complex pathogen profile of compound datasets. We compared Afanc against currently available cutting edge profilers using 3 datasets: single species read sets simulated from the full Mycobacteriaceae taxonomic landscape; compound read sets containing multiple Mycobacteriaceae species and variants; and real data covering the majority of the M. tuberculosis lineage taxonomic space. Afanc outperformed all profilers, both generic and Mycobacteriaceae specific, across all tested fields. As a species agnostic profiler, we predict that Afanc will be of great utility when carrying out highly specific and sensitive pathogen profiling of clinical datasets. Such analyses are essential in advising both the clinical response to an individual disease case, and in forming the foundation of epidemiological surveys.

bioinformatics↗