ArticleGenomics, proteomics & bioinformatics2021
PM2RA: A Framework for Detecting and Quantifying Relationship Alterations in Microbial Community.
Article in Genomics, proteomics & bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- An integrative multi-omics approach identifies microbiome alterations linked to pathological and behavioral features in autism spectrum disorder.Cell reports. Medicine · 2026Article
- Probiotics derived sodium benzoate improves social behavior of offspring exposed in the maternal immune activation through regulation of histone lysine benzoylation in astrocytes.Molecular psychiatry · 2025Article
- Resilience of human gut microbiomes in autism spectrum disorder: measured using stiffness network analysis.Microbiology spectrum · 2025Article
- mbDriver: identifying driver microbes in microbial communities based on time-series microbiome data.Briefings in bioinformatics · 2024Article
- Impacts of Dietary Standardized Ileal Digestible Lysine to Net Energy Ratio on Lipid Metabolism in Finishing Pigs Fed High-Wheat Diets.Animals : an open access journal from MDPI · 2024Article
- Relationship between gut microbiota and Chinook salmon (Frontiers in microbiology · 2023Article
- CDEMI: Characterizing differences in microbial composition and function in microbiome data.Computational and structural biotechnology journal · 2023Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The dysbiosis of gut microbiota is associated with the pathogenesis of human diseases. However, observing shifts in the microbe abundance cannot fully reveal underlying perturbations. Examining the relationship alterations (RAs) in the microbiome between health and disease statuses provides additional hints about the pathogenesis of human diseases, but no methods were designed to detect and quantify the RAs between different conditions directly. Here, we present profile monitoring for microbial relationship alteration (PM2RA), an analysis framework to identify and quantify the microbial RAs. The performance of PM2RA was evaluated with synthetic data, and it showed higher specificity and sensitivity than the co-occurrence-based methods. Analyses of real microbial datasets showed that PM2RA was robust for quantifying microbial RAs across different datasets in several diseases. By applying PM2RA, we identified several novel or previously reported microbes implicated in multiple diseases. PM2RA is now implemented as a web-based application available at http://www.pm2ra-xingyinliulab.cn/.
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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.