openomics 0.8.8

This Python package provide a series of tools to integrate and query the genomics, transcriptomics, proteomics, and clinical data (aka multi-omics data). With 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

Features

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

Citations

The journal paper for this scientific package is currently being reviewed. In the meanwhile, the current package version can be cited with:

# BibTeX
@software{nhat_jonny_tran_2021_4552831,
  author       = {Nhat Tran and
                  Jean Gao},
  title        = {{BioMeCIS-Lab/OpenOmics: Bug fixes from pyOpenSci
                   Reviewer 2}},
  month        = feb,
  year         = 2021,
  publisher    = {Zenodo},
  version      = {v0.8.5},
  doi          = {10.5281/zenodo.4552831},
  url          = {https://doi.org/10.5281/zenodo.4552831}
}

Credits

This package was created with Cookiecutter and the pyOpenSci/cookiecutter-pyopensci project template, based off audreyr/cookiecutter-pypackage.