Skip to main content

Mummichog

Mummichog is a Python program for analyzing data from high throughput, untargeted metabolomics. It leverages the organization of metabolic networks to predict functional activity directly from feature tables, bypassing metabolite identification. The features include

  • computing significantly enriched metabolic pathways
  • identifying significant modules in the metabolic network
  • visualization of top networks in web browser
  • visualization that also plugs into Cytoscape
  • tentative annotations
  • metabolic models for different species through plugins

This is mummichog package version 2. Version 3 is under development.

Please note that mummichog-server is a different package/repository.

Installation

Mummichog can be installed using pip (pip Installs Packages), the Python package manager. The command below will install the default (version 2):

pip install mummichog

This is OS independent. To read more on pip here.

One can also run mummichog without installing it. Direct python call on a downloaded copy can work, e.g.

python3 -m mummichog.main -f mummichog/tests/testdata0710.txt -o t2

Use custom metabolic model

The -n argument now (v2.6) takes user specified metabolic model in JSON format, e.g.

python3 -m mummichog.main -n mummichog/tests/metabolicModel_RECON3D_20210510.json -f mummichog/tests/testdata0710.txt -o t3

The porting of metabolic model is demonstrated here https://github.com/shuzhao-li/Azimuth/blob/master/docs/

Please note that identifier conversion is a major issue in genome scale models. Users benefit greatly from including chemical formula (neutral_formula) and molecular weight (neutral_mono_mass) in the model.

History

Python 3 is required for Mummichog version 2.3 and beyond.

Mummichog version 2.2 was the last version using Python 2; new branch as mummichog-python2

The initial paper on mummichog is described in Li et al. Predicting Network Activity from High Throughput Metabolomics. PLoS Computational Biology (2013); doi:10.1371/journal.pcbi.1003123.

More on project website http://mummichog.org.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mummichog-2.6.1.tar.gz (5.3 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mummichog-2.6.1-py3-none-any.whl (6.6 MB view details)

Uploaded Python 3

File details

Details for the file mummichog-2.6.1.tar.gz.

File metadata

  • Download URL: mummichog-2.6.1.tar.gz
  • Upload date:
  • Size: 5.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.22.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.37.0 CPython/3.7.4

File hashes

Hashes for mummichog-2.6.1.tar.gz
Algorithm Hash digest
SHA256 de9048fd548d73ec13430c2a8c98e567ece79cece9b444b78470c76584b8ba2e
MD5 821adebaedf2a0380d20cafa4956387a
BLAKE2b-256 c76003f3b553a393e75f057d08813fbf5a459f535507b6d128834a93cb742abb

See more details on using hashes here.

File details

Details for the file mummichog-2.6.1-py3-none-any.whl.

File metadata

  • Download URL: mummichog-2.6.1-py3-none-any.whl
  • Upload date:
  • Size: 6.6 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.22.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.37.0 CPython/3.7.4

File hashes

Hashes for mummichog-2.6.1-py3-none-any.whl
Algorithm Hash digest
SHA256 77799396464fdf87088cee5819b127d4ae1f047a2e8461a66ede0ac7f043646e
MD5 fa122a2106bf6417be011a3cd8df6022
BLAKE2b-256 3712cd278fb5800cfe833b4edb220083558a8b8310abc700cc6cb9c3a76af7e1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page