MiCoNE - Microbial Co-occurrence Network Explorer
MiCoNE is a Python package for the exploration of the effects of
various possible tools used during the 16S data processing workflow on
the inferred co-occurrence networks. It is also developed as a flexible
and modular pipeline for 16S data analysis, offering parallelized, fast
and reproducible runs executed for different combinations of tools for
each step of the data processing workflow. It incorporates various
popular, publicly available tools as well as custom Python modules and
scripts to facilitate inference of co-occurrence networks from 16S data.
Free software: MIT license
The MiCoNE framework is introduced in:
Kishore, D., Birzu, G., Hu, Z., DeLisi, C., Korolev, K., & Segrè, D. (2023). Inferring microbial co-occurrence networks from amplicon data: A systematic evaluation. mSystems. doi:10.1128/msystems.00961-22.
Data related to the publication can be found on Zenodo: https://doi.org/10.5281/zenodo.7051556.
Plug and play architecture: allows easy additions and removal of new tools
Flexible and portable: allows running the pipeline on local machine, compute cluster or the cloud with minimal configuration change through the usage of nextflow
Parallelization: automatic parallelization both within and across samples (needs to be enabled in the
Ease of use: available as a minimal
Pythonlibrary (without the pipeline) or as a full
If you have a version of
juliathat is preinstalled, make sure that it does not conflict with the version downloaded by the
The data directory (
nf_micone/data) needs to be manually downloaded using this link.
Table of Contents
- Example pipeline setup and execution
- Data Import and Export (Python API)