Evidence map›Paper›PMID 39975011›Full record

ArticlebioRxiv : the preprint server for biology2025

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

Michal Ziemski, Liz Gehret, Anthony Simard, Santiago Castro Dau, Vinzent Risch, Doriela Grabocka, Christos Matzoros, Colin Wood, Paula Momo Cabrera, Rodrigo Hernández-Velázquez and 6 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Michal ZiemskiDepartment of Health Sciences and Technology, ETH Zurich, Switzerland.ORCID 0000-0001-6285-8852
Liz GehretPathogen and Microbiome Institute, Northern Arizona University, USA.
Anthony SimardPathogen and Microbiome Institute, Northern Arizona University, USA.
Santiago Castro DauDepartment of Health Sciences and Technology, ETH Zurich, Switzerland.
Vinzent RischDepartment of Health Sciences and Technology, ETH Zurich, Switzerland.
Doriela GrabockaDepartment of Health Sciences and Technology, ETH Zurich, Switzerland.
Christos MatzorosDepartment of Health Sciences and Technology, ETH Zurich, Switzerland.
Colin WoodPathogen and Microbiome Institute, Northern Arizona University, USA.
Paula Momo CabreraDepartment of Health Sciences and Technology, ETH Zurich, Switzerland.
Rodrigo Hernández-VelázquezDepartment of Health Sciences and Technology, ETH Zurich, Switzerland.
Chloe HermanPathogen and Microbiome Institute, Northern Arizona University, USA.
Keegan EvansPathogen and Microbiome Institute, Northern Arizona University, USA.
Michael S RobesonUniversity of Arkansas for Medical Sciences, Department of Biomedical Informatics, Little Rock, AR, USA.ORCID 0000-0001-7119-6301
Evan BolyenPathogen and Microbiome Institute, Northern Arizona University, USA.
J Gregory CaporasoPathogen and Microbiome Institute, Northern Arizona University, USA.ORCID 0000-0002-8865-1670
Nicholas A BokulichDepartment of Health Sciences and Technology, ETH Zurich, Switzerland.ORCID 0000-0002-1784-8935

Funding

Advanced Development of Informatics Technologies for Cancer Research and Management (U24 Clinical Trial Optional)U24CA248454 · NCI · NORTHERN ARIZONA UNIVERSITY · PI CAPORASO, JAMES GREGORY · 2020 to 2024
$3.7M
NCI NIH HHS U24 CA248454
6 · The paper itself

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.

Identifiers

PMID39975011
PMCPMC11838374

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.