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.


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

Website GitHub Conda Paper


User-Friendly R Package for Supervised Machine Learning Pipelines

Website GitHub CRAN Conda Paper

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.