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OpenOmics provides a bioinformatics API and web-app platform integrate and visualize the multiomics and clinical data.

Project description

PyPI version Documentation Status pyOpenSci status DOI OpenOmics codecov

OpenOmics is currently under active development and we may break API compatibility in the future.

This Python package provide a series of tools to integrate and explore the genomics, transcriptomics, proteomics, and clinical data (aka multi-omics data). With interfaces to popular annotation databases and scalable data-frame manipulation tools, OpenOmics facilitates the common data wrangling tasks when preparing data for RNA-seq bioinformatics analysis.

Documentation (Latest | Stable) | OpenOmics at a glance


OpenOmics assist in integration of heterogeneous multi-omics bioinformatics data. The library provides a Python API as well as an interactive Dash web interface. It features support for:

  • Genomics, Transcriptomics, Proteomics, and Clinical data.
  • Harmonization with 20+ popular annotation, interaction, disease-association databases.

OpenOmics also has an efficient data pipeline that bridges the popular data manipulation Pandas library and Dask distributed processing to address the following use cases:

  • Providing a standard pipeline for dataset indexing, table joining and querying, which are transparent and customizable for end-users.
  • Providing Efficient disk storage for large multi-omics dataset with Parquet data structures.
  • Integrating various data types including interactions and sequence data, then exporting to NetworkX graphs or data generators for down-stream machine learning.
  • Accessible by both developers and scientists with a Python API that works seamlessly with an external Galaxy tool interface or the built-in Dash web interface (WIP).

Installation via pip:

$ pip install openomics


The journal paper for this scientific package was reviewed by JOSS at, and can be cited with:

# BibTeX
  doi = {10.21105/joss.03249},
  url = {},
  year = {2021},
  publisher = {The Open Journal},
  volume = {6},
  number = {61},
  pages = {3249},
  author = {Nhat C. Tran and Jean X. Gao},
  title = {OpenOmics: A bioinformatics API to integrate multi-omics datasets and interface with public databases.},
  journal = {Journal of Open Source Software}


Thank you for extremely helpful feedback and guidance from the pyOpenSci reviewers. This package was created with the pyOpenSci/cookiecutter-pyopensci project template, based off audreyr/cookiecutter-pypackage.

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