High-throughput pipeline for de-novo assembly and drug resistance mutations identification from Next-Generation Sequencing viral data of residual diagnostic samples

BioRxiv : the Preprint Server for Biology
Tiziano Gallo CassarinoPaul Kellam


Motivation: The underlying genomic variation of a large number of pathogenic viruses can give rise to drug resistant mutations resulting in treatment failure. Next generation sequencing (NGS) enables the identification of viral quasi-species and the quantification of minority variants in clinical samples; therefore, it can be of direct benefit by detecting drug resistant mutations and devising optimal treatment strategies for individual patients. Results: The ICONIC (InfeCtion respONse through vIrus genomiCs) project has developed an automated, portable and customisable high-throughput computational pipeline to assemble de novo whole viral genomes, either segmented or non-segmented, and quantify minority variants using residual diagnostic samples. The pipeline has been benchmarked on a dedicated High-Performance Computing cluster using paired-end reads from RSV, HIV and Influenza clinical samples. The median length of generated genomes was 82% for the HIV dataset and 100% for each Influenza segment. The analysis of each set lasted less than 12 hours; each sample took around 3 hours and required a maximum memory of 10 GB. The pipeline can be easily ported to a dedicated server or cluster through either an installation script or ...Continue Reading

Related Concepts

Computer Software
Treatment Protocols
Pathogenic Organism
Influenza virus vaccine
Gene Mutation
Viral Oncolysate
HIV Infections

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