iq-GHOST

iq-GHOST implements the General Heterogeneous evolution On a Single Topology (GHOST) model under a maximum-likelihood framework to infer phylogenetic trees from molecular sequence data exhibiting heterotachous evolution.

Key Features:

• Heterotachous Evolution Handling: Accounts for heterotachous evolution, where different sites change rates over time, using the GHOST model.
• Maximum-Likelihood Framework: Uses a maximum-likelihood approach to estimate tree topology, branch lengths, and substitution model parameters.
• Empirical Data Performance: Recovers accurate phylogenetic trees under simulated heterotachous conditions and has been validated on datasets including plastome alignments and phylogenomic data sets.
• Biological Insights: Minimizes restrictive model constraints to reveal historical signals such as convergent evolution, exemplified by electric organ evolution in distinct lineages of electric fish.

Scientific Applications:

• Phylogenomic Analysis: Applied to large phylogenomic datasets to resolve deep relationships, including results that place turtles as sister to archosaurs.
• Convergent Evolution Studies: Compares GHOST model inferences to traditional models to identify components of convergent evolution.
• Gene-Specific Inference: Applied to specific gene datasets, such as sodium channel genes across multiple taxa, to reveal evolutionary patterns.

Methodology:

Implements the GHOST model within IQ-TREE under a maximum-likelihood framework and compares performance to traditional variable rates-across-sites models.