Single Cell in the Cloud Codeathon, Jan 15-17 at NYGC

Single Cell in the Cloud Codeathon, Jan 15-17 at NYGC

NCBI is pleased to announce a single-cell focused codeathon at the New York Genome Center,  January 15 -17. To apply, please complete the application form by December 30, 2019. Read on if you need more information about the event.

When and where is the codeathon?

January 15-17, 2020 at the New York Genome Center in New York City .

Who can participate?

We encourage researchers and data scientists at any stage of their data science journey to apply.  Teams will greatly benefit from people who possess any of the following skills:

  • analyzing single cell data types
  • working knowledge of scripting (e.g., Shell, Python, R)
  • familiarity with methods for manipulating and/or analyzing large datasets
  • developing bioinformatics code, pipelines or tools
  • data visualization

There is no registration fee associated with attending this event.

Note: You must bring your own laptop. We do not offer financial support for travel, lodging, or meals for this event.

What are some of the potential team projects?

  • Using single-cell SRA sequence to verify/improve submitted metadata available in SRA.
  • Assessing log-transformation and z-scores for scRNA-seq data analysis.
  • Identifying bulk RNA-seq-derived biomarkers of cancer risk within single-cell populations.
  • Defining Cell Fate Regulators in Multi-omic Single Cell Developmental Datasets.
  • Identifying rapid cleavage sites from scRNA-seq data.
  • Understanding cancer evolution through single cell expression dynamics.
  • Using Tabula Muris Senis as a reference for a semi-automated sc-RNA-seq analysis workflow in the cloud.

How are teams formed?

Before the event, we will create five to eight teams, consisting of five to six individuals each with various backgrounds and expertise. Each team will be led by an experienced leader.

What will a typical day be like?

We will meet from 9 am to 5 pm each day, with the potential to extend into the evening hours for continued work or optional social events.

Each day, we will gather as a group for a short presentation on a hot topic of interest to the data science and bioinformatics community such as bioinformatics best practices, coding styles, etc. and then break out to work on team project pipelines and tools for the analysis of large datasets within a cloud infrastructure. On each day, teams will present short talks to introduce their project (day 1), discuss project progress (day 2), and present the results.

What will we build?

We will make all pipelines, other scripts, software, and programs generated in this codeathon available on a dedicated public GitHub repository.

Teams may submit manuscripts describing the design and use of the software tools they created  to an appropriate journal such as the F1000Research hackathons channelBMC BioinformaticsGigaScienceGenome Research, or PLoS Computational Biology.

How to apply?

To apply, please complete the application form.  Applications are due December 30th, 2019 by 3 p.m. EST. We will select participants based on their experience and their motivation to attend.

We encourage prior participants and prior applicants to apply. We will notify the first round of accepted applicants on January 3, 2020. Accepted applicants have until January 8 at noon ET to confirm their participation. International applicants or those with particular skill sets may be accepted early. If you confirm, please make sure that you can attend, as confirming and not attending prevents other scientists from attending this event. Please provide a monitored email address, in case we have follow-up questions.


Participants retain ownership of all intellectual property rights (including moral rights) in the code submitted to as well as developed in the codeathon. Employees of the U.S. Government attending as part of their official duties retain no copyright in their work and their work is in the public domain in the U.S. The Government disclaims any rights in the code submitted or developed in the codeathon. Participants agree to publish the code and any related data on GitHub.

Please contact Allissa Dillman if you have questions or need more information.


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