Software and Resources
We develop free, open-source bioinformatics software and data resources for analyzing microbiome "omics" datasets. For a complete list of our software and resources, see our GitHub profiles.
Open-source projects on GitHub:
Research software: external page https://github.com/bokulich-lab/
Educational resources: external page https://github.com/fsb-edu/
Code/data linked to publications: external page https://github.com/bokulich-publications/
Selected Software:
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QIIME 2 is a microbiome multi-omics bioinformatics and data science platform that is trusted, free, open source, extensible, and community developed and supported.
Website: external page https://qiime2.org/
Publication: external page https://doi.org/10.1038/s41587-019-0209-9
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MOSHPIT is a comprehensive toolkit of plugins for whole metagenome assembly, annotation, and analysis built on the microbiome multi-omics data science framework QIIME 2. MOSHPIT enables flexible, modular, fully reproducible workflows for read-based or assembly-based analysis of metagenome data.
Website: external page https://moshpit.readthedocs.io/
Publication: external page https://doi.org/10.1101/2025.01.27.635007
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RESCRIPt is a python 3 package to support a variety of operations for managing and curating reference sequence databases, DNA/RNA sequence data, and taxonomic data, built on the QIIME 2 framework for fully reproducible, provenance-tracked reference database curation and management.
Website: external page https://github.com/bokulich-lab/RESCRIPt/
Publication: external page https://doi.org/10.1371/journal.pcbi.1009581
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q2-fondue (Functions for reproducibly Obtaining and Normalizing Data re-Used from Elsewhere) is a QIIME 2 plugin for programmatic access to sequences and metadata from NCBI Sequence Read Archive (SRA). It enables user-friendly acquisition, re-use, and management of public nucleotide sequence (meta)data while adhering to open data principles.
Website: external page https://github.com/bokulich-lab/q2-fondue
Publication: external page https://doi.org/10.1093/bioinformatics/btac639
Selected Resources:
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FermDB is an open database and dashboard of information about global fermented foods. This comprises the largest manually curated database of fermented food information, classified according to source and substrate origin.
Website: external page https://bokulich-lab.github.io/FermDB/
Publication: external page https://doi.org/10.1016/j.tifs.2024.104569
Educational Resources
Python Basic (for Food Scientists): Notebooks for self-paced training in Python programming. Designed for food scientists or anyone who wants to learn Python. external page https://fsb-edu.github.io/PythonBook/
Data Visualization Best Practices (for Food Scientists): Notebooks for self-paced training in data visualization best practices. Designed with food scientists in mind, or anyone who wants to learn about data visualization best practices. external page https://fsb-edu.github.io/DataVisualizationBook/
ML4Food: Jupyter notebooks for self-paced introduction to machine learning. Designed with food scientists in mind, but these serve as a gentle introduction to machine learning that can be appropriate for beginners in any field. external page https://github.com/fsb-edu/ML4Food