Gallo Cassarino, T;
Sugar, R;
Kozlakidis, Z;
Kellam, P;
Frampton, D;
(2016)
High-throughput pipeline for the de novo viral genome assembly and the identification of minority variants from Next-Generation Sequencing of residual diagnostic samples.
BioRxiv: Cold Spring Harbor, NY, USA.
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Abstract
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 and Influenza clinical samples. The median length of generated genomes was 96% for the RSV 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 a docker image. As it enables the subtyping of viral samples and the detection of relevant drug resistance mutations within three days of sample collection, our pipeline could operate within existing clinical reporting time frames and potentially be used as a decision support tool towards more effective personalised patient treatments. / Availability: The software and its documentation are available from https://github.com/ICONIC-UCL/pipeline / Contact: t.cassarino{at}ucl.ac.uk, pk5{at}sanger.ac.uk / Supplementary information: Supplementary data are available at Briefings in Bioinformatics online.
| Type: | Working / discussion paper |
|---|---|
| Title: | High-throughput pipeline for the de novo viral genome assembly and the identification of minority variants from Next-Generation Sequencing of residual diagnostic samples |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1101/035154 |
| Publisher version: | https://doi.org/10.1101/035154 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10075339 |
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