GenomeKit genomic data

Description

GenomeKit is Deep Genomics’ Python library for fast and easy access to genomic resources such as sequence, data tracks, and annotations. The goal is to let machine learning researchers build data sets easily, and to be creative about how those data sets are designed. Out of the box, GenomeKit provides access to pre-built optimized genomic data files that are required for its operation.

Update Frequency

Data is updated when popular new genome versions (assemblies or annotations) are released

License

Apache License Version 2.0 https://www.apache.org/licenses/LICENSE-2.0

Documentation

https://deepgenomics.github.io/GenomeKit/data_org.html

Managed By

Deep Genomics

See all datasets managed by Deep Genomics.

Contact

https://github.com/deepgenomics/GenomeKit/issues

How to Cite

GenomeKit genomic data was accessed on DATE from https://registry.opendata.aws/genomekit.

Usage Examples

Tutorials

• Quickstart by Deep Genomics
  

Tools & Applications

• An RNA foundation model enables discovery of disease mechanisms and candidate therapeutics by Albi Celaj, Alice Jiexin Gao, Tammy T.Y. Lau, Erle M. Holgersen, Alston Lo, Varun Lodaya, Christopher B. Cole, Robert E. Denroche, Carl Spickett, Omar Wagih, Pedro O. Pinheiro, Parth Vora, Pedrum Mohammadi-Shemirani, Steve Chan, Zach Nussbaum, Xi Zhang, Helen Zhu, Easwaran Ramamurthy, Bhargav Kanuparthi, Michael Iacocca, Diane Ly, Ken Kron, Marta Verby, Kahlin Cheung-Ong, Zvi Shalev, Brandon Vaz, Sakshi Bhargava, Farhan Yusuf, Sharon Samuel, Sabriyeh Alibai, Zahra Baghestani, Xinwen He, Kirsten Krastel, Oladipo Oladapo, Amrudha Mohan, Arathi Shanavas, Magdalena Bugno, Jovanka Bogojeski, Frank Schmitges, Carolyn Kim, Solomon Grant, Rachana Jayaraman, Tehmina Masud, Amit Deshwar, Shreshth Gandhi, Brendan J. Frey