PyIOmica (pyiomica) is a Python package for omics analyses.

Last update: Jun 29, 2022

Overview

PyIOmica (pyiomica)

This repository contains PyIOmica, a Python package that provides bioinformatics utilities for analyzing (dynamic) omics datasets. PyIOmica extends MathIOmica usage to Python and implements new visualizations and computational tools for graph analyses. The documentation is available at Read the Docs: https://pyiomica.readthedocs.io/en/latest/

PyIOmica Installation Instructions

A. INSTALLATION

Pre-Installation Requirements

 To install PyIOmica on any platform you need Python version 3.7 or higher

Installation Instructions

To install the current release from PyPI (Python Package Index) use pip:

pip install pyiomica

Alternatively, you can install directly from github using:

pip install git+https://github.com/gmiaslab/pyiomica/

git clone https://github.com/gmiaslab/pyiomica/
python setup.py install

B. RUNNING PyIOmica

After installation you can run:

>>> import pyiomica

C. DOCUMENTATION

Documentation for PyIOmica is built-in and is available through the help() functionality in Python. Also the documentation is available at Read the Docs: https://pyiomica.readthedocs.io/en/latest/

D. ADDITIONAL INFORMATION

PyIOmica is a multi-omics analysis framework distributed as a Python package that aims to assist in bioinformatics.
The most current version of the package is maintained at https://github.com/gmiaslab/pyiomica
News are distributed via twitter (@mathiomica)

E. LICENSING

PyIOmica is released under an MIT License. Please also consult the folder LICENSES distributed with PyIOmica regarding Licensing information for use of external associated content.

F. OTHER CONTACT INFORMATION

G. Mias Lab (https://georgemias.org)
e-mail: [email protected]
twitter: @mathiomica

G. FUNDING

PyIOmica development and associated research were supported by the Translational Research Institute for Space Health through NASA Cooperative Agreement NNX16AO69A (Project Number T0412, PI: Mias). The content is solely the responsibility of the authors and does not necessarily represent the official views of the supporting funding agencies.

I. CITATIONS

If you use PyIOmica in your work please use the following citation:
- Sergii Domanskyi, Carlo Piermarocchi and George I Mias, PyIOmica: longitudinal omics analysis and trend identification. Bioinformatics, 36(7), 2306–2307 (2020). https://doi.org/10.1093/bioinformatics/btz896
If you use PyIOmica's visibility graph functionality, please also consider the following citation:
- Minzhang Zheng, Sergii Domanskyi, Carlo Piermarocchi, and George I Mias, Visibility graph based temporal community detection with applications in biological time series, Sci Rep 11, 5623 (2021). https://doi.org/10.1038/s41598-021-84838-x

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Comments

add 1 module, 2 functions and 1 examples

add module "visibilityGraphCommunityDetection"

add functions of PlotNVGBarGraph_Dual, PlotHVGBarGraph_Dual at module "visualizationFunctions"

add examples examplesVisibilityGraphCommunityDetection.py

opened by MZZheng 0

Releases(1.3.3)

1.3.3(Nov 28, 2021)

Updated visibility graph community detection function to optionally output community times.
Source code(tar.gz)
Source code(zip)
1.3.2(Nov 28, 2021)

New release addresses compatibility with Reactome API (ReactomeAnalysis).
Source code(tar.gz)
Source code(zip)
1.3.1(Aug 25, 2021)

Update output of clustering object to spreadsheets
Source code(tar.gz)
Source code(zip)
1.3.0(Jun 28, 2021)

Added customization options for visualization functions. Corrected typos/bugs.
Source code(tar.gz)
Source code(zip)
1.2.9(Jun 8, 2021)

Updated function names for visibility graph plotting (lower case first lettering for consistency).
Source code(tar.gz)
Source code(zip)
1.2.8(Jun 8, 2021)

This release has updated main functions to consistently use camelCase, and updated documentation strings - see changelog for function details.
Source code(tar.gz)
Source code(zip)
1.2.7(Jun 8, 2021)

Added additional functionality for comparing multiple subjects
Source code(tar.gz)
Source code(zip)
1.2.6(Mar 16, 2021)

Minor update to autocorrelation function to better handle nan values.
Source code(tar.gz)
Source code(zip)
1.2.5(Feb 15, 2021)

Minor update to visibility graph community detection functions
Source code(tar.gz)
Source code(zip)
1.2.4(Dec 29, 2020)

Minor update to allow custom plot labels in categorization heatmaps
Source code(tar.gz)
Source code(zip)
1.2.3(Oct 19, 2020)

PyIOmica 1.2.3 is compatible with Python 3.7+
Source code(tar.gz)
Source code(zip)
1.2.1(Apr 25, 2020)

PyIOmica 1.2.1 is compatible with Python 3.7+
Source code(tar.gz)
Source code(zip)
1.2.0(Feb 28, 2020)

PyIOmica 1.2.0 is compatible with Python 3.7+
Source code(tar.gz)
Source code(zip)
1.1.2(Nov 20, 2019)

PyIOmica 1.1.2 is compatible with Python 3.7+
Source code(tar.gz)
Source code(zip)
1.1.1(Oct 26, 2019)

PyIOmica 1.1.1 is compatible with Python 3.7+
Source code(tar.gz)
Source code(zip)
1.1.0(Oct 24, 2019)

PyIOmica 1.1.0 is compatible with Python 3.7+
Source code(tar.gz)
Source code(zip)
1.0.2(Jul 29, 2019)

PyIOmica 1.0.2 is compatible with Python 3.7+
Source code(tar.gz)
Source code(zip)
1.0.1(Jul 29, 2019)

PyIOmica 1.0.1 is compatible with Python 3.7+
Source code(tar.gz)
Source code(zip)
1.0.0(Jul 19, 2019)

PyIOmica version 1.0.0 compatible with Python 3.7+
Source code(tar.gz)
Source code(zip)

Owner

G. Mias Lab

GitHub Repository https://pyiomica.readthedocs.io/en/latest/

PyIOmica (pyiomica) is a Python package for omics analyses.

Related tags

Overview

PyIOmica (pyiomica)

PyIOmica Installation Instructions

A. INSTALLATION

Pre-Installation Requirements

Installation Instructions

B. RUNNING PyIOmica

C. DOCUMENTATION

D. ADDITIONAL INFORMATION

E. LICENSING

F. OTHER CONTACT INFORMATION

G. FUNDING

I. CITATIONS

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Comments

add 1 module, 2 functions and 1 examples

Releases(1.3.3)

1.3.3(Nov 28, 2021)

1.3.2(Nov 28, 2021)

1.3.1(Aug 25, 2021)

1.3.0(Jun 28, 2021)

1.2.9(Jun 8, 2021)

1.2.8(Jun 8, 2021)

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1.1.2(Nov 20, 2019)

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1.1.0(Oct 24, 2019)

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Owner

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