Evidence map›Paper›PMID 39753610›Full record

ArticleScientific reports2025

Key features and guidelines for the application of microbial alpha diversity metrics.

Ignacio Cassol, Mauro Ibañez, Juan Pablo Bustamante

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 5 pooled it
–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

100 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Impacts of Lifestyle and Microbiota-Targeted Interventions for Overweight and Obesity on the Human Gut Microbiome: A Systematic Review.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
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  8. Humanizing Zophobas morio larvae microbiota for rapid screening of emerging decolonization strategies against multidrug-resistant bacteria.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
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40 more citing papers are in PubMed but not listed here.

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

3 authors.

Ignacio Cassol *Facultad de Ingeniería, Universidad Austral, LIDTUA, CIC, Buenos Aires, Argentina.
Mauro Ibañez *Facultad de Ingeniería, Universidad Nacional de Entre Ríos, Oro Verde, Argentina.
Juan Pablo BustamanteFacultad de Ingeniería, Universidad Austral, LIDTUA, CIC, Buenos Aires, Argentina. jbustamante@austral.edu.ar.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies of microbial communities vary widely in terms of analysis methods. In this growing field, the wide variety of diversity measures and lack of consistency make it harder to compare different studies. Most existing alpha diversity metrics are inherited from other disciplines and their assumptions are not always directly meaningful or true for microbiome data. Many existing microbiome studies apply one or some alpha diversity metrics with no fundamentals but also an unclear results interpretation. This work focuses on a theoretical, empirical, and comparative analysis of 19 frequently and less-frequently used microbial alpha diversity metrics grouped into 4 proposed categories, including key features of every analyzed metric with their mathematical assumptions, to provide a deeper understanding of the existing metrics and a practical implementation guide for future studies. Key metrics that should be required in microbiome analysis include richness, phylogenetic diversity, entropy, dominance of a few microbes over others, and an estimate of unobserved microbes. Collectively, these metrics contribute to a comprehensive set of analyses characterizing samples, allowing the determination of key aspects that might be otherwise obscured by partial or biased information. These guidelines enable further detailed analysis by each author according to their specific interests and clinical trials. Several practical examples are provided to illustrate how these recommendations improve the quality and depth of information obtained, facilitating better interpretation when working with microbiome data. These guidelines can be applied to both existing and future research studies, enhancing the standardization, consistency, and robustness of the analyses conducted. This approach aims to improve the capture of biological diversity, leading to better interpretations and insights.

Indexed as

BiodiversityMicrobiotaPhylogenyBacteriaGuidelines as TopicHumans

Identifiers

PMID39753610
PMCPMC11698868

What OpenQuestion holds

Textmetadata
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.