ArticleMicroorganisms2023
MPrESS: An R-Package for Accurately Predicting Power for Comparisons of 16S rRNA Microbiome Taxa Distributions including Simulation by Dirichlet Mixture Modeling.
Article in Microorganisms, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Beyond Infection: How Antimicrobial Therapies Influence the Urinary Microbiome and Stone Disease.Pharmaceuticals (Basel, Switzerland) · 2025Review
- New insights into the cultivability of human milk bacteria from ingestion to digestion and implications for their Immunomodulatory properties.Scientific reports · 2025Article
- Semisynthetic simulation for microbiome data analysis.Briefings in bioinformatics · 2024Review
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Deep sequencing has revealed that the 16S rRNA gene composition of the human microbiome can vary between populations. However, when existing data are insufficient to address the desired study questions due to limited sample sizes, Dirichlet mixture modeling (DMM) can simulate 16S rRNA gene predictions from experimental microbiome data. We examined the extent to which simulated 16S rRNA gene microbiome data can accurately reflect the diversity within that identified from experimental data and calculate the power. Even when experimental and simulated datasets differed by less than 10%, simulation by DMM consistently overestimates power, except when using only highly discriminating taxa. Admixtures of DMM with experimental data performed poorly compared to pure simulation and did not show the same correlation with experimental data
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Registered trials
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.