MiSurv

MiSurv performs integrated analysis of microbiome composition and survival data to test associations, compare treatment groups, and build predictive models of survival responses.

Key Features:

• Data Processing Module: Preprocesses and standardizes microbiome datasets for downstream analyses.
• Comparative Survival Analysis (Module 1): Performs comparative survival analysis between treatment groups (e.g., new vs. old treatment, treatment vs. placebo) to assess effects on disease progression over time.
• Microbial Composition Comparison (Module 2): Compares microbial composition across treatment groups to identify taxa-level changes associated with treatments.
• Association Testing (Module 3): Tests associations between microbial composition and survival responses to identify taxa correlated with patient outcomes.
• Prediction Modeling (Module 4): Builds prediction models using microbial taxa to forecast survival responses.

Scientific Applications:

• Clinical trials: Evaluates temporal dynamics of disease progression and treatment effects on survival within clinical trial datasets.
• Type 1 diabetes (T1D) studies: Analyzes gut microbiome changes and survival or onset risk in T1D, including investigations of antibiotic use on T1D onset and gut microbiome composition.
• Biomarker discovery: Identifies microbial taxa that correlate with survival outcomes as potential biomarkers.
• Predictive stratification: Develops microbial-taxa-based predictive models for forecasting survival responses and informing treatment stratification hypotheses.

Methodology:

Microbiome data preprocessing and standardization; comparative survival analysis between treatment groups; microbial composition comparison across groups; association testing between microbial composition and survival responses; and prediction modeling using microbial taxa to forecast survival responses.