TCGenerators

TCGenerators generates and analyzes binary tree-child (BTC) phylogenetic networks to represent and study reticulate evolutionary events such as hybridization and horizontal gene transfer.

Key Features:

• Efficient Network Generation: Generates all possible BTC networks for a specified number of leaves using reduction and augmentation operations.
• Recursive Algorithm: Implements a recursive generation method that provides a recurrence relation and an upper bound on the number of BTC networks for a given leaf count.
• Extension of Evolutionary Histories: Extends BTC networks to include new sequences, enabling updates to evolutionary histories as data are added.
• Implementation in Python: Algorithms are implemented in Python.
• Computational Experiments: Provides computational experiments that demonstrate the method's functionality and evaluate its behavior.

Scientific Applications:

• Reticulate Evolution: Models hybridization and horizontal gene transfer to reconstruct phylogenies that include reticulate events.
• Phylogenomic Studies: Supports incorporation of new sequences into BTC networks for large-scale phylogenomic analyses.
• Comparative Genomics: Enables comparison of evolutionary histories across species or genes using BTC network representations.

Methodology:

Reduction/augmentation operations and a recursive generation algorithm that yields a recurrence relation used to establish an upper bound on the number of BTC networks.