PyHGNC Documentation

for version: 0.2.4

PyHGNC is a python software interface developed by the Department of Bioinformatics at the Fraunhofer Institute for Algorithms and Scientific Computing SCAI for the data provided by the European Bioinformatics Institute (EMBL-EBI) on their HGNC website. Thanks to the significant and important work of the HUGO Gene Nomenclature Committee the scientific community has an essential standardised nomenclature for human genes in hand. Because in many software projects a local installation with fast programmatic access is required, we have developed a Python library which allows to access and query HGNC data locally with very limited programming skills.

For the impatient user: on your console

pip install pyhgnc
pyhgnc update

... in your Python console

import pyhgnc
query = pyhgnc.query()

The content of HGNC made easy accessible by PyHGNC supports successfully scientists in the IMI funded projects AETIONOMY and PHAGO. It is used for the identification of potential drugs in complex disease networks with several thousand relationships compiled from BEL statements.

Aim of this software project is to provide an programmatic access to locally stored HGNC data and allow a filtered export in several formats used in the scientific community. Query functions allow to search in the data and use it as pandas.DataFrame in Jupyter notebooks. We will focus our software development on the analysis and extension of biological disease knowledge networks. PyHGNC is an ongoing project and needs improvement. We are happy if you want to support our project or start a scientific cooperation with us.

ToDo: Add Figure of PyHGNC ER

Fig. 1: ER model of PyHGNC database

_images/imi_logo.png _images/aetionomy_logo.png _images/scai_logo.svg

Acknowledgment and contribution to scientific projects

Software development by:

The software development of PyHGNC by Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) is supported and funded by the IMI (INNOVATIVE MEDICINES INITIATIVE) projects AETIONOMY and PHAGO. The aim of both projects is the identification of mechnisms in Alzhiemer’s and Parkinson’s disease in complex biological BEL networks for drug development.

Indices and Tables