VirusLab: A Tool for Customized SARS-CoV-2 Data Analysis

Abstract

Since the beginning of 2020, the COVID-19 pandemic has posed unprecedented challenges to viral data analysis and connected host disease diagnostic methods. We propose VirusLab, a flexible system for analysing SARS-CoV-2 viral sequences and relating them to metadata or clinical information about the host. VirusLab capitalizes on two existing resources: ViruSurf, a database of public SARS-CoV-2 sequences supporting metadata-driven search, and VirusViz, a tool for visual analysis of search results. VirusLab is designed for taking advantage of these resources within a server-side architecture that: (i) covers pipelines based on approaches already in use (ARTIC, Galaxy) but entirely cutomizable upon user request; (ii) predigests analysis of raw sequencing data from different platforms (Oxford Nanopore and Illumina); (iii) gives access to public archives datasets; (iv) supplies user-friendly reporting – making it a tool that can also be integrated into a business environment. VirusLab can be installed and hosted within the premises of any organization where information about SARS-CoV-2 sequences can be safely integrated with information about hosts (e.g., clinical metadata). A system such as VirusLab is not currently available in the landscape of similar providers: our results show that VirusLab is a powerful tool to generate tabular/graphical and machine readable reports that can be integrated in more complex pipelines. We foresee that the proposed system can support many research-oriented and therapeutic scenarios within hospitals or the tracing of viral sequences and their mutational processes within organizations for viral surveillance.

Semantic interoperability: ontological unpacking of a viral conceptual model

“…Consider, for instance, a scenario where a hospital with COVID-19 patients is interested in assessing their clinical phenotype, possibly annotating the collected swab tests with additional information regarding the specific SARS-CoV-2 variant and the presence of given mutations with known effects [18]. Tools such as SnpEff [79], CorGAT [80], or the Coronavirus Typing Tool [81] may be used for annotating the viral information, within protected environments such as VirusLab [82]. A correct ontological characterization of concepts is necessary for 1) interpreting all the aspects related to the production of virus sequence, 2) establishing a correct host-virus link, and 3) supporting effective interoperability [17], thereby enabling the design of models that correlate clinical outcomes with the characteristics of the virus.…”

High Performance Integration Pipeline for Viral and Epitope Sequences

“…VirusViz is designed to explore the isolates in our repository, but can also import external datasets described as a Multi-FASTA file for the nucleotide sequences, plus an additional CSV file for metadata; in this case, a simplified version of the pipeline hereby presented (including sequence analysis and basic metadata identification) processes the external sequences and produces gene annotations, protein annotations, amino acid changes, nucleotide variations, and prediction of functional effects. A copy of our pipeline is also powering VirusLab [ 3 ], a private version of VirusViz, designed to be used in environments with strict privacy concerns, such as hospitals, for analyzing the viral sequences sampled from local patients.…”

“…More recently, the system has been extended with EpiSurf [ 2 ] to also include epitope region annotations, and with VirusViz and VirusLab, two visualization interfaces. While in our previous works [ 1 , 2 , 3 ] we primarily discussed the features of the systems ViruSurf, EpiSurf, and VisusLab from the user’s perspective, in this manuscript we intend to address the technological aspects behind their realization. Moreover, after almost two years since the launch of ViruSurf and EpiSurf and millions of sequences integrated, we can now prove the scalability of the methods adopted, especially in light of the 64× increase in the volume of SARS-CoV-2 sequences registered during the year 2021.…”

Interoperability of COVID-19 Clinical Phenotype Data with Host and Viral Genetics Data

“…VirusViz allows partitioning the population of interest into groups and comparatively visualizing their mutation distributions, with several options for highlighting positions, mutational patterns, and regions of interests. VirusViz has a dual close-source solution, i.e., VirusLab [12], commercialized by the Quantia Consulting S.R.L. company and developed in collaboration with our group at Politecnico di Milano, within the EIT project N. 20663.…”