BCC2020

→ Abstract


The presenter(s) will be available for live Q&A in this session (BCC West).

S. Ciccolella*, L. Denti*, P. Bonizzoni, G. Della Vedova, Y. Pirola**, M. Previtali**

Dept. of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy.

E-mail: yuri.pirola@unimib.it
*Joint First Authors.
**Joint Last Authors.

Project Website: https://algolab.github.io/MALVIRUS/
Source Code: https://github.com/algolab/malvirus
License: GNU General Public License version 3

The SARS-CoV-2 pandemic has put the global health care services to the test and many researchers are racing to face its swift and rapid spread. The availability of efficient approaches to analyze variations from the growing amount of sequencing data daily produced is of the utmost importance.

We introduce MALVIRUS, an easy-to-install and easy-to-use web application that assists users in computing a SNP catalog extracted from the sequences of a viral population and in efficiently calling variants of the catalog that are in a read sample. MALVIRUS implements a pipeline divided in two modules, based on four state-of-the-art open source tools. The first module uses MAFFT and snp-sites to compute the SNP catalog from the input set of sequences whereas the second module uses KMC3 and MALVA to call the genotypes from the input read sample. MALVIRUS is designed to work with viral populations and viral high-coverage read samples. Tests on Illumina and Nanopore samples sequenced from SARS-CoV-2 strains prove the efficiency and the effectiveness of MALVIRUS in genotyping viral strains with respect to the SNP catalog extracted from GISAID data.

MALVIRUS is released under the GPL3 license and is available as a self-hosted web application. It is distributed as a Docker image and it uses open source platforms as backbone, such as Snakemake for pipeline executions and Bioconda for package management. These technologies will enable us to scale MALVIRUS to public clouds or computing infrastructures and offer it as a public service. The web interface is composed by a Flask backend and a React JS frontend. The entire application can be easily installed using "docker run -p 56733:80 -v mvjobs:/jobs algolab/malvirus". Then, once the Docker container is running, MALVIRUS is easily accessible through your preferred web browser at http://localhost:56733/.

The computed genotypes can be viewed from the web interface or can be downloaded as VCF or ODS files for further processing. An extensive documentation for the entire process from the installation to the examination of the results is available at https://algolab.github.io/MALVIRUS/ together with a detailed tutorial.