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Peer-reviewedCC BYCell Genomics

MOSHPIT: Accessible, reproducible metagenome data science on the QIIME 2 framework

  • Michał Ziemski1
  • Liz Gehret1
  • Anthony Simard2
  • Santiago Castro Dau1
  • Vinzent Risch1
  • Doriela Grabocka1
  • Christos Konstantinos Matzoros1
  • Colin Wood2
  • Paula Momo Cabrera1
  • Rodrigo Hernández-Velázquez1
  • Milo R. Schärer1
  • Felicia Sandberg1
6 more authors
  • Chloe Herman2
  • Keegan Evans2
  • Michael Scott Robeson3
  • Evan Bolyen1
  • J. Gregory Caporaso4
  • Nicholas A. Bokulich5
5 affiliations
  1. 1Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
  2. 2Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ 86011, USA
  3. 3University of Arkansas for Medical Sciences, Department of Biomedical Informatics, Little Rock, AR 72205, USA
  4. 4Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ 86011, USA; Translational Genomics Research Institute, Flagstaff, AZ 86011, USA
  5. 5Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland. Electronic address: [email protected]
Open at sourceDOICite

Abstract

Metagenome sequencing has revolutionized functional microbiome analysis across diverse ecosystems, but is fraught with technical hurdles. We introduce MOSHPIT (https://moshpit.readthedocs.io), software built on the QIIME 2 framework (Q2F) that integrates best-in-class CAMI2-validated metagenome tools with robust provenance tracking and multiple user interfaces, enabling streamlined, reproducible metagenome analysis for all expertise levels. By building on Q2F, MOSHPIT enhances scalability, interoperability, and reproducibility in complex workflows, democratizing and accelerating discovery at the frontiers of metagenomics.

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Cite

BibTeXRIS
BibTeX
@article{ziemski2026moshpit,
  title = {{MOSHPIT: Accessible, reproducible metagenome data science on the QIIME 2 framework}},
  author = {Michał Ziemski and Liz Gehret and Anthony Simard and Santiago Castro Dau and Vinzent Risch and Doriela Grabocka and Christos Konstantinos Matzoros and Colin Wood and Paula Momo Cabrera and Rodrigo Hernández-Velázquez and Milo R. Schärer and Felicia Sandberg and Chloe Herman and Keegan Evans and Michael Scott Robeson and Evan Bolyen and J. Gregory Caporaso and Nicholas A. Bokulich},
  journal = {Cell Genomics},
  year = {2026},
  month = sep,
  doi = {10.1016/j.xgen.2026.101366},
  url = {https://doi.org/10.1016/j.xgen.2026.101366},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - MOSHPIT: Accessible, reproducible metagenome data science on the QIIME 2 framework
AU  - Michał Ziemski
AU  - Liz Gehret
AU  - Anthony Simard
AU  - Santiago Castro Dau
AU  - Vinzent Risch
AU  - Doriela Grabocka
AU  - Christos Konstantinos Matzoros
AU  - Colin Wood
AU  - Paula Momo Cabrera
AU  - Rodrigo Hernández-Velázquez
AU  - Milo R. Schärer
AU  - Felicia Sandberg
AU  - Chloe Herman
AU  - Keegan Evans
AU  - Michael Scott Robeson
AU  - Evan Bolyen
AU  - J. Gregory Caporaso
AU  - Nicholas A. Bokulich
PY  - 2026
DA  - 2026/09/24
JO  - Cell Genomics
DO  - 10.1016/j.xgen.2026.101366
UR  - https://doi.org/10.1016/j.xgen.2026.101366
AB  - Metagenome sequencing has revolutionized functional microbiome analysis across diverse ecosystems, but is fraught with technical hurdles. We introduce MOSHPIT (https://moshpit.readthedocs.io), software built on the QIIME 2 framework (Q2F) that integrates best-in-class CAMI2-validated metagenome tools with robust provenance tracking and multiple user interfaces, enabling streamlined, reproducible metagenome analysis for all expertise levels. By building on Q2F, MOSHPIT enhances scalability, interoperability, and reproducibility in complex workflows, democratizing and accelerating discovery at the frontiers of metagenomics.
SN  - 2666-979X
ER  -