PRJNA234451
A cloud-compatible bioinformatics pipeline for ultra-rapid pathogen identification from next-generation sequencing of clinical samples
Unbiased next-generation sequencing (NGS) approaches enable comprehensive pathogen detection in the clinical microbiology laboratory, and have numerous applications for public health surveillance, outbreak investigation, and the diagnosis of infectious diseases. However, practical NGS deployment of the technology is hindered by the bioinformatics challenge of analyzing results accurately and in a clinically relevant timeframe. Here we describe SURPI (sequence-based ultra-rapid pathogen identification), a computational pipeline for pathogen identification from complex metagenomic NGS data generated from clinical samples. Deployable on both cloud-based and standalone servers, SURPI leverages two state-of-the-art aligners for accelerated analyses, SNAP and RAPSearch, which are as accurate as existing bioinformatics tools but orders of magnitude faster in performance. In fast mode, SURPI detects viruses and bacteria by scanning datasets of 7 - 500 million reads in 11 minutes - 5 hours, while in comprehensive mode, all known microorganisms are identified, followed by de novo assembly and protein homology searches for divergent viruses in 50 minutes – 16 hours. To date, SURPI has been used for pathogen identification in over 960 clinical samples comprising more than 9 billion sequences, and has directly contributed to real-time actionable diagnosis of infections in acutely ill patients.