Welcome to danRerLib’s Documentation
Introduction
Welcome to danRerLib’s Documentation page! danRerLib, short for Danio rerio library, is a comprehensive toolkit designed specifically for zebrafish researchers, focusing on genomics and transcriptomics.
Getting Started
New to danRerLib? Start with our Introduction page to learn about the toolkit’s features.
User’s Guide
Explore the user’s guide to discover how to make the most of danRerLib:
Installation: Step-by-step instructions on how to install the toolkit.
Usage Principles: Learn the core principles and best practices for using danRerLib effectively.
API Reference
For detailed information on danRerLib’s APIs and modules, check out our API reference:
API Reference Home: Explore the Python API reference documentation for full functionality.
Tutorials
Learn by doing with our hands-on tutorials:
Gene ID Mapping: A how-to guide for gene ID mapping.
Orthology Mapping: A how-to guide for orthology mapping.
Enrichment Testing: A how-to guide for enrichment testing.
Workflow: A reproducible workflow for enrichment testing in danRerLib.
Developer Guide
If you’re interested in contributing or want to learn more about the toolkit’s development:
Changelog: Stay up-to-date with the latest changes and updates.
Contributing: Join our community and contribute to danRerLib’s development.
Code of Conduct: Familiarize yourself with our code of conduct.
License: license.
Publication Information
danRerLib has been published in Bioinformatics Advances under the title danRerLib: a python package for zebrafish transcriptomics. The full publication can be found here.
Citation
Ashley V Schwartz, Karilyn E Sant, Uduak Z George, danRerLib: a python package for zebrafish transcriptomics, Bioinformatics Advances, 2024;, vbae065, https://doi.org/10.1093/bioadv/vbae065.
Development
danRerLib
has been developed by the SDSU Computational Toxicology Laboratory with primary Python code contributions from Ashley Schwartz. Karilyn E. Sant and Uduak Z. George conceived the study.
Funding
This work was supported by a National Institute of Health (National Institute of Diabetes and Digestive and Kidney Diseases) award [1R21DK134931-01 to U.Z.G and K.E.S]. Support for K.E.S. was also provided by the National Institute of Environmental Health Sciences [K01ES031640]. Support for U.Z.G was also provided by a National Science Foundation CAREER award [DMS2240155]. A.V.S. acknowledges support from the San Diego Achievement Rewards for College Scientists Foundation and the College of Sciences at San Diego State University.
Disclaimer
“Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding organizations.”