NCBI’s Virus Discovery Hackathon: Engaging Research Communities to Identify Cloud Infrastructure Requirements

Abstract

A wealth of viral data sits untapped in publicly available metagenomic data sets when it might be extracted to create a usable index for the virological research community. We hypothesized that work of this complexity and scale could be done in a hackathon setting. Ten teams comprised of over 40 participants from six countries, assembled to create a crowd-sourced set of analysis and processing pipelines for a complex biological data set in a three-day event on the San Diego State University campus starting 9 January 2019. Prior to the hackathon, 141,676 metagenomic data sets from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) were pre-assembled into contiguous assemblies (contigs) by NCBI staff. During the hackathon, a subset consisting of 2953 SRA data sets (approximately 55 million contigs) was selected, which were further filtered for a minimal length of 1 kb. This resulted in 4.2 million (Mio) contigs, which were aligned using BLAST against all known virus genomes, phylogenetically clustered and assigned metadata. Out of the 4.2 Mio contigs, 360,000 contigs were labeled with domains and an additional subset containing 4400 contigs was screened for virus or virus-like genes. The work yielded valuable insights into both SRA data and the cloud infrastructure required to support such efforts, revealing analysis bottlenecks and possible workarounds thereof. Mainly: (i) Conservative assemblies of SRA data improves initial analysis steps; (ii) existing bioinformatic software with weak multithreading/multicore support can be elevated by wrapper scripts to use all cores within a computing node; (iii) redesigning existing bioinformatic algorithms for a cloud infrastructure to facilitate its use for a wider audience; and (iv) a cloud infrastructure allows a diverse group of researchers to collaborate effectively. The scientific findings will be extended during a follow-up event. Here, we present the applied workflows, initial results, and lessons learned from the hackathon.

League of Brazilian Bioinformatics: a competition framework to promote scientific training

“…Indeed, connecting students to problem solving challenges has been an approach that has demonstrated such an improvement in the ability to conduct research while expanding their opportunities to be absorbed by different sectors of industry and market (Pathanasethpong et al, 2019;Mason et al, 2009). With the gradual increase of professionals in Bioinformatics and the specialization that is requested, competitions for knowledge in this area began to arise (Kienzler and Fontanesi, 2017;Lawson et al, 2020;Connor et al, 2019;Pathanasethpong et al, 2019;Wang et al, 2018;Silver et al, 2016). Furthermore, hackathons have been applied in specific areas to explore public data, increase educational and innovation opportunities, create biological insights (2019 Model "Metrics" Challenge, Health Hackathons and NCBI's Virus Discovery Hackathon), and even solve new challenges and improve the state of the art (AlQuraishi, 2019;Zhou et al, 2019;Lawson et al, 2020).…”

NCBI’s Virus Discovery Codeathon: Building “FIVE” —The Federated Index of Viral Experiments API Index

“…Data accessibility and data federation, the virtualization of sparse databases into a common platform, represent the most important assets to the wider scientific community. There have been previous attempts to federate such databases and to make them open access, specifically for viral sequences [ 4 ].…”

“…SRA serves as an umbrella for a variety of sequencing experiments (e.g., amplicons, whole genome sequencing, and environmental metagenomics) from different platforms (namely IonTorrent, Illumina, Oxford Nanopore, and PacBio) and applications. The first collaborative attempt to annotate and index SRA datasets in bulk was conducted as part of the inaugural of this series of events, the Virus Hunting Toolkit (VHT) [ 4 ]. This first event (VHT-1) challenged users to harness the power of the Google Cloud environment to test and develop bioinformatics pipelines to identify all viruses, including previously characterized and novel, in existing publicly available SRA datasets.…”

“…The working groups were organized by specific tasks to emphasize the exhaustive separation of known viral diversity from the bulk data, and the identification of possible new viral sequences: data selection, taxonomic and cluster identification, and annotation of domains and genes. From that first codeathon, a set of 5.5 × 10 7 reassembled contigs, from 2953 SRA entries, were produced (see Table 1 on accessing these resources) [ 4 ]. All contigs were classified and annotated, and this information was integrated into a complete dataset [ 9 ].…”

“…This novel resource indexes sequences, metadata, and hyperdata from the VHT-1 hackathon, sparse databases, and online resources. More than 2953 SRA entries assembled during VHT-1 [ 4 ] were reanalyzed and their annotations included in FIVE. Additionally, existing databases (i.e., taxonomy, CRISPR, etc.)…”