Ananke

Ananke clusters marker-gene data by temporal correlation to identify ecologically meaningful temporal patterns in microbial communities.

Key Features:

• Time-series clustering: Clusters marker-gene data collected over time according to temporal correlation to reveal ecological dynamics such as seasonal variation and organism appearance or disappearance.
• Complementary to sequence-identity clustering: Provides an alternative perspective to OTU- or taxonomy-based clustering by prioritizing temporal behavior over genetic similarity.
• Detection of OTU inconsistencies: Identifies internal OTU inconsistencies by comparing temporal profiles within and between OTUs.
• Simulation and analysis of ecological patterns: Employs algorithms to simulate and analyze multiple ecological patterns, including periodic seasonal dynamics.

Scientific Applications:

• Human gut microbiome: Segregated fecal bacterial communities sampled over one year from an individual and detected temporal shifts associated with events such as food poisoning.
• Freshwater lake communities: Applied to an eleven-year marker-gene time series to show that high sequence identity does not necessarily predict similar temporal dynamics and to reveal patterns obscured by taxonomy- or sequence-based methods.

Methodology:

Ananke employs advanced algorithms to simulate and analyze multiple ecological patterns, including periodic seasonal dynamics, and clusters marker-gene data by temporal correlation rather than by sequence identity.