Software

We develop software tools to help us analyze multi-omics data and make sense of the microbial world. All of our code is open source and available on Github. Click on the badges below to learn more about the software we develop.

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mothur

Command-Line Tool for Processing 16S rRNA Gene Sequence Data

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mikropml

User-Friendly R Package for Supervised Machine Learning Pipelines

An interface to build machine learning models for classification and regression problems. mikropml implements the ML pipeline described by Topçuoğlu et al. (2020) with reasonable default options for data preprocessing, hyperparameter tuning, cross-validation, testing, model evaluation, and interpretation steps. See the website for more information, documentation, and examples.

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schtools

Schloss Lab Tools for Reproducible Microbiome Research 💩

A collection of useful functions and example code created and used by the Schloss Lab for reproducible microbiome research. Perform common tasks like read output files from mothur, tidy up your microbiome data, and format rmarkdown documents for publication. See the website for more information, documentation, and examples.