Cronos

Cronos analyzes microbial time-series at the community level to detect community clusters, track transitions between community states, and predict future microbial configurations.

Key Features:

• Community-Based Analysis: Operates on the premise that microbial communities form distinct clusters with similar compositions at each time point, enabling community-level interpretation of dynamics.
• Cluster Detection and Transition Tracking: Detects intrinsic microbial profile clusters across sampled time points, describes their composition, and records transitions between these states.
• Predictive Modeling: Integrates cluster assignments with associated metadata to model transitions between community states and predict future community configurations under varying conditions.

Scientific Applications:

• Ecological studies of complex microbiomes: Provides insight into community-level dynamics where analyses of individual taxa are insufficient, including responses to environmental or physiological stimuli.
• Infant gut microbiome development: Applied to growing infants to reveal distinct developmental trajectories for breastfed versus formula-fed infants and their convergence toward mature-like profiles.

Methodology:

Implemented in R. Inputs comprise a microbial composition table (e.g., OTU table), a phylogenetic tree depicting relationships, and relevant metadata. The workflow identifies clusters of similar microbial compositions at each time point, tracks transitions between these clusters over time, and uses metadata with cluster assignments to model and predict future community states.