PhyInformR

PhyInformR calculates phylogenetic informativeness to evaluate sequence data utility and screen datasets for phylogenetic information content and propensity for convergent or parallel evolution.

Key Features:

• Advanced theoretical framework: Implements phylogenetic informativeness-based theory to predict the utility of sequence data across dataset partitions.
• Support for uneven branch lengths and nucleotide substitution models: Accommodates uneven branch lengths and any model of nucleotide substitution when assessing informativeness.
• Bayesian quartet resolution: Calculates quartet internode resolution probabilities within a Bayesian framework to account for phylogenetic uncertainty.
• Optimized computational efficiency: Uses optimized statistical routines and parallel processing for rapid, high-throughput screening of phylogenetic/genomic information content.
• Data visualization: Provides tools for visualizing phylogenetic informativeness and relationships derived from sequence data.

Scientific Applications:

• Screening for convergent or parallel evolution: Identifies molecular sites and dataset partitions with propensity toward convergent or parallel evolution.
• Experimental design and marker evaluation: Incorporates phylogenetic uncertainty to inform sampling strategies and marker choice for phylogenetic studies.
• Phylogenetic analysis of large-scale and next-generation sequencing data: Evaluates informativeness and resolution potential across large-scale sequence and next-generation sequence datasets.
• Assessment of internode resolution: Estimates quartet internode resolution probabilities to evaluate expected phylogenetic resolution.

Methodology:

Calculates phylogenetic informativeness using phylogenetic informativeness theory; accommodates uneven branch lengths and any nucleotide substitution model; computes quartet internode resolution probabilities in a Bayesian framework; and employs optimized statistical calculations with parallel processing for high-throughput analyses.