Evidence map›Paper›PMID 41049561›Full record

ArticleF1000Research2025

Facilitating bootstrapped and rarefaction-based microbiome diversity analysis with q2-boots.

Isaiah Raspet, Elizabeth Gehret, Chloe Herman, Jeff Meilander, Andrew Manley, Anthony Simard, Evan Bolyen, J Gregory Caporaso

Abstract read
In one paragraph

Article in F1000Research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Late-in-life treadmill training mitigates gut microbiome imbalances and cardiovascular disease risk in mice.American journal of physiology. Gastrointestinal and liver physiology · 2026
    Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Isaiah RaspetPathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, 86011, USA.
Elizabeth GehretPathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, 86011, USA.
Chloe HermanPathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, 86011, USA.
Jeff MeilanderPathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, 86011, USA.ORCID https://orcid.org/0009-0005-4519-1896
Andrew ManleyPathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, 86011, USA.
Anthony SimardPathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, 86011, USA.
Evan BolyenPathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, 86011, USA.
J Gregory CaporasoPathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, 86011, USA.ORCID https://orcid.org/0000-0002-8865-1670

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

Background: We present q2-boots, a QIIME 2 plugin that facilitates bootstrapped and rarefaction-based microbiome diversity analysis. This plugin provides eight new actions that allow users to apply any of thirty different alpha diversity metrics and twenty-two beta diversity metrics to bootstrapped or rarefied feature tables, using a single QIIME 2 Pipeline command, or more granular QIIME 2 Action commands. Results: Given a feature table, an even sampling depth, and the number of iterations to perform ( n), the command qiime boots core-metrics will resample the feature table n times and compute alpha and beta diversity metrics on each resampled table. The results will be integrated in summary data artifacts that are identical in structure and type to results that would be generated by applying diversity metrics to a single table. This enables all the same downstream analytic tools to be applied to these tables and ensures that all collected data is considered when computing microbiome diversity metrics. Conclusions: A challenge of this work was deciding how to integrate distance matrices that were computed on n resampled feature tables, as a simple average of pairwise distances (median or mean) does not account for the structure of distance matrices. q2-boots provides three options, and we show here that the results of these approaches are highly correlated. q2-boots is free and open source. Source code can be found at https://github.com/caporaso-lab/q2-boots; installation instructions and a tutorial can be found in the project's documentation at https://q2-boots.readthedocs.io.

Indexed as

Computational BiologyMicrobiotaSoftwareBiodiversityHumansbootstrapmicrobiomeQIIME 2rarefaction

Identifiers

PMID41049561
PMCPMC12489448

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.