We are pleased to announce the second installment of the SoCal Bioinformatics Hackathon. From January 9-11, 2019, the NCBI will help run a bioinformatics hackathon in Southern California hosted by the Computational Sciences Research Center at San Diego State University!
We’re specifically looking for folks who have experience in computational virus hunting or adjacent fields to identify known, taxonomically-definable and novel viruses from a few hundred thousand metagenomic datasets that we’ll put on cloud infrastructure. This event is for researchers, including students and postdocs, who are already engaged in the use of bioinformatics data or in the development of pipelines for virological analyses from high-throughput experiments. If this describes you, please apply! The event is open to anyone selected for the hackathon and willing to travel to SDSU (see below).
Working groups of five to six individuals will be formed into five to eight teams. These teams will build pipelines to analyze large datasets within a cloud infrastructure. The projects will be unveiled before the hackathon starts and will build off previous NCBI hackathons.
After a brief organizational session, teams will spend three days developing a virological index and discovering novel viruses in a group of metagenomic datasets. Participants will analyze and combine datasets to work on these problems. We will be writing code and solving problems.
Throughout the three days, we will break out to discuss progress on each of the topics, bioinformatics best practices, coding styles, etc.
Datasets will come from public repositories, with a focus on metagenomics datasets in the Sequence Read Archive (SRA) that have been ported to cloud infrastructure, as well as derivative contigs of the above.
All pipelines and other scripts, software, and programs generated in this hackathon will be added to a public GitHub repository designed for that purpose.
Manuscripts describing the design and usage of the software tools constructed by each team may be submitted to an appropriate journal such as the F1000Research hackathons channel, BMC Bioinformatics, GigaScience, Genome Research or PLoS Computational Biology. Ideally, we will release a virological index based on the findings from expansive, merged datasets on cloud infrastructure.
San Diego State University
Founded in 1897, San Diego State University (SDSU) is a public institution of higher education located in Southern California. SDSU is the oldest and largest university in San Diego and the third largest in the state.
To apply, please complete this form (approximately 5 minutes to complete). Initial applications are due Wednesday, December 12th, 2018 by 3 pm PT. Participants will be selected based on the experience and motivation they provide on the form.
Prior participants and applicants are especially encouraged to apply. The first round of accepted applicants will be notified on December 14 by 3 pm PT and have until December 17 at noon PT to confirm their participation. If you confirm, please make sure it is highly likely you can attend, as not attending after confirmation prevents other data scientists from attending this event. Please include a monitored email address in case you or the organizers have follow-up questions.
Requirements: Participants will need to bring their own laptop to this event. A working knowledge of scripting (e.g., Shell, Python, R) is useful but not necessary to be successful in this event. Employment of higher level scripting or programming languages may also be useful.
Applicants must be willing to commit to all three days of the event.
No financial support for travel, lodging or meals is available for this event. Also, note that the hackathon may extend into the evening hours each day. Please make any necessary arrangements to accommodate this possibility. Depending on the number of people that need accommodation, we will attempt to get a group rate at one of the local hotels. Please indicate on the registration form if you need a hotel room.
There will be no registration fee or cost associated with attending this event.