cocci-call: a species-aware variant identification pipeline forCoccidioidesspp. in genomic epidemiology
Authors: Marchetti Marco , Fonseca Emanuel M. , Hanson Kimberly E. , Barker Bridget , Walter Katharine S. 
Published: January 2025

ABSTRACTEmerging fungal pathogens, such asCoccidioides, the causative agent of Valley fever, pose significant clinical and public health challenges. While advances in genomic epidemiology have enhanced our understanding ofCoccidioidesevolutionary history, the lack of standardized tools for variant identification makes it difficult to draw comparisons between studies. To address this gap, we developed and benchmarked a novel, publicly available pipeline, cocci-call, designed for genome-wide variant identification and species assignment. We found that cocci-call correctly identifiesCoccidioidesspecies in 100% (20/20)in silicosequence read sets and 98.86% (173/175) clinical or environmental samples. We found that performance of variant identification significantly improved when focusing on high-confidence genomic benchmarking regions. For example, the F1 score increased from 63.9% to 93.8% forC. posadasiiand 60.2% to 84.7%C. immitis, respectively, when moving from a whole-genome analysis to gene-only analysis. We observed a similar trend when repetitive regions were masked. Empirical sequencing of theC. posadasiiNR-166 reference strain corroborated these findings, with cocci-call achieving an F1 score of 63.9% in whole-genome analysis and 93.8% in gene-only regions. These results underscore the robustness and utility of cocci-call forCoccidioidesgenomic analyses, making it a valuable tool for genome-wide association studies and phylogenetics ofCoccidioides.DATA SUMMARYRaw sequencing data generated for this study are available in the Sequence Read Archive (SRA) under BioSample SAMN45887705. This includes whole-genome sequencing data used for variant identification and benchmarking, as well as sequencing data from clinical and environmental Coccidioides samples. The pipeline cocci-call, developed for species-aware variant identification inCoccidioidesspp., is publicly available athttps://github.com/ksw9/cocci-call. All scripts and code used for the analysis performed in this study are included in the pipeline repository.IMPACT STATEMENTCoccidioidomycosis or Valley fever, caused by the fungal pathogensCoccidioidesspp., is a growing public health concern. Understanding the genetic diversity of these pathogens is vital for tracking infections, improving diagnostics, and guiding effective treatments. Despite its public health importance, the lack of standardized tools for analyzingCoccidioidesgenomes has hindered the comparability of findings across studies. To address this challenge, we developed and measured the performance of cocci-call, an open-source pipeline for species assignment and variant identification. By establishing a standardized approach, cocci-call facilitates cross-study comparisons, enhances collaboration among research groups, and contributes to a deeper understanding of pathogen evolution and transmission dynamics. Ultimately, our study supports global efforts to combat fungal infections and protect public health by providing a consistent, benchmarked framework for genomic research.