Mirage 2.0

Mirage 2.0 estimates gene-content evolutionary history by modeling heterogeneous evolutionary patterns among gene families.

Key Features:

• Deterministic Pattern Mixture Model: Implements a deterministic pattern mixture model to represent heterogeneous evolutionary patterns across gene families.
• Speed and Memory Efficiency: Enhances computational speed and memory efficiency for processing large datasets.
• Scalability: Scales to datasets comprising thousands of genomes for large-scale genomic analyses.

Scientific Applications:

• Gene-content Reconstruction: Reconstructs gene-content evolution across species by accounting for family-specific evolutionary patterns.
• Comparative Genomics: Enables comparative genomics analyses on large collections of genomes.
• Phylogenetic Analyses: Supports phylogenetic analyses that incorporate gene family gain and loss dynamics.
• Gene Family Diversification Studies: Investigates molecular mechanisms underlying gene family diversification by resolving heterogeneous evolutionary trajectories.
• Evolutionary Biology: Aids studies of genome evolution dynamics across lineages.

Methodology:

Mirage 2.0 uses a deterministic pattern mixture model to account for heterogeneous evolutionary patterns among gene families.