Welcome to the Microbiome
Centers Consortium (MCC)

All Microbes. All the time.

Learn More About Us

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  • R for Data Science

    Free R for Data Science textbook.

  • About

    About

    Our Vision & Mission We envision a holistic approach to microbiome research that shares and builds on knowledge across ecological systems and scientific disciplines to improve ecosystem and human health. Facilitate collaboration and knowledge exchange among researchers. Engage with the broader scientific community and the public to raise awareness about microbiome research. Provide resources and…

  • Qiita

    open-source microbial study management platform

  • TidyVerse

    An open source set of resources in R to organize data

  • KBase Educators Community

    For educators using KBase (kbase.us) in their curriculum — Join to access community-developed resources for teaching with KBase, supportive documentation, and best practices.

  • Bioinformatics Virtual Coordination Network

    Welcome to the website for the Bioinformatics Virtual Coordination Network (BVCN). The group was started in March 2020 in response to the COVID-19 pandemic. As research laboratories were shutting, we, a group of bioinformaticians and computational biologists, sought to formalize training to helping wet-lab biologists pick up some computational skills/begin computational projects during the global…

  • The Ohio Super Computer – Tutorials for Unix / HPC

    Tutorials on Unix and High Performance Clustering (HPC). Some are more on how to use OSC, too.

  • National Microbiome Data Collaborative

    Introducing the National Microbiome Data Collaborative (NMDC), an initiative to empower the research community to harness microbiome data exploration and discovery through a collaborative integrative data science ecosystem.

  • Miaverse

    R/Bioc methods, benchmarking data, and educational material for microbiome research

  • Anvi’o

    Anvi’o is a comprehensive platform that brings together many aspects of today’s cutting-edge computational strategies of data-enabled microbiology, including genomics, metagenomics, metatranscriptomics, pangenomics, metapangenomics, phylogenomics, and microbial population genetics in an integrated and easy-to-use fashion through extensive interactive visualization capabilities.