Next Article in Journal
Expression of ZNF695 Transcript Variants in Childhood B-Cell Acute Lymphoblastic Leukemia
Previous Article in Journal
The Global Prader–Willi Syndrome Registry: Development, Launch, and Early Demographics
Previous Article in Special Issue
Two Years of Viral Metagenomics in a Tertiary Diagnostics Unit: Evaluation of the First 105 Cases
genes-logo
Article Menu

Article Menu

Open AccessArticle

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

1
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda MD 20894, USA
2
Charles Perkins Centre, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
3
KU Leuven, Department of Microbiology & Immunology, Rega Institute, Leuven BE3000, Belgium
4
Department of Biology, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182, USA
5
Lab of Cellular Oncology, NCI, NIH, Bethesda, MD 20892-4263, USA
6
Research Group on Computational Biology and Microbial Ecology, Department of Biological Sciences, Universidad de los Andes, Bogotá 111711, Colombia
7
Max Planck Tandem Group in Computational Biology, Universidad de los Andes, Bogotá 111711, Colombia
8
D’Amour & Associates, 11839 Hilltop Drive, Los Altos Hills, CA 94024, USA
9
Department of Genetics, University Medical Center Groningen, Groningen 9713AV, The Netherlands
10
Computational Bioscience Program, University of Colorado Anschutz, Aurora, CO 80045, USA
11
Bioinformatics and Systems Biology Program, University of California at San Diego, 9500 Gilman Dr., La Jolla, CA 92093, USA
12
Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
13
Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
14
Department of Laboratory Medicine, University of Washington Virology, 1616 Eastlake Ave E, Seattle, WA 98102, USA
15
Department of Biosystems Engineering, University of Arizona, Tucson, AZ 85716, USA
16
MITRE Corporation, 7515 Colshire Drive, McLean, VA 22102-7539, USA
17
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
18
University of Tsukuba, Ibaraki 305-8575, Japan
19
Boyce Thompson Institute, Ithaca, NY 14853, USA
20
Bioscience Division, Los Alamos National Lab, Los Alamos, NM 87545, USA
21
Center for Dark Energy Biosphere Investigations, University of Southern California, Los Angeles, CA 90089, USA
22
School of Natural Sciences, University of California Merced, Merced, CA 95343, USA
*
Author to whom correspondence should be addressed.
Genes 2019, 10(9), 714; https://doi.org/10.3390/genes10090714
Received: 26 July 2019 / Revised: 5 September 2019 / Accepted: 5 September 2019 / Published: 16 September 2019
(This article belongs to the Special Issue Viral Diagnostics Using Next-Generation Sequencing)
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. View Full-Text
Keywords: metagenomic; viruses; SRA; STRIDES; hackathon; infrastructure; cloud computing metagenomic; viruses; SRA; STRIDES; hackathon; infrastructure; cloud computing
Show Figures

Figure 1

MDPI and ACS Style

Connor, R.; Brister, R.; Buchmann, J.P.; Deboutte, W.; Edwards, R.; Martí-Carreras, J.; Tisza, M.; Zalunin, V.; Andrade-Martínez, J.; Cantu, A.; D’Amour, M.; Efremov, A.; Fleischmann, L.; Forero-Junco, L.; Garmaeva, S.; Giluso, M.; Glickman, C.; Henderson, M.; Kellman, B.; Kristensen, D.; Leubsdorf, C.; Levi, K.; Levi, S.; Pakala, S.; Peddu, V.; Ponsero, A.; Ribeiro, E.; Roy, F.; Rutter, L.; Saha, S.; Shakya, M.; Shean, R.; Miller, M.; Tully, B.; Turkington, C.; Youens-Clark, K.; Vanmechelen, B.; Busby, B. NCBI’s Virus Discovery Hackathon: Engaging Research Communities to Identify Cloud Infrastructure Requirements. Genes 2019, 10, 714.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop