PM2RA

PM2RA detects and quantifies alterations in microbial community relationships across conditions to characterize perturbations in microbiome structure beyond abundance shifts.

Key Features:

• Methodology: PM2RA employs Hotelling’s T² statistics to project multi-dimensional microbial community data into a one-dimensional space and quantify relationship alterations (RAs) between two or more microbes across different conditions.
• Performance and Efficiency: The method was evaluated on synthetic datasets and demonstrated superior specificity and sensitivity compared to co-occurrence-based methods, with an average processing time of 30 minutes for datasets containing 100 features on a Linux system with 8 processors.
• Robustness Across Datasets: PM2RA was tested on real microbial datasets across various diseases and consistently quantified microbial RAs across different contexts.
• Research Applications: PM2RA identifies previously reported and novel microbes implicated in multiple diseases, providing insights into the pathogenesis of human diseases associated with gut microbiota dysbiosis and supporting research on complex microbial interactions.

Scientific Applications:

• Disease pathogenesis: Identification of microbes implicated in multiple diseases and investigation of gut microbiota dysbiosis in human disease.
• Microbial interaction analysis: Quantification of relationship alterations to study complex interactions within microbial communities and their implications for health and disease.
• Benchmarking and method comparison: Evaluation on synthetic datasets for specificity and sensitivity comparisons with co-occurrence-based methods.

Methodology:

PM2RA uses Hotelling’s T² statistics to project multi-dimensional microbial community data into a one-dimensional space and quantify relationship alterations between two or more microbes across conditions.