ClinePlotR

ClinePlotR provides R functions to visualize and analyze genomic clines, quantifying multi-locus differentiation across hybrid zones and locus-specific transitions in admixed genomes relative to genome-wide trends.

Key Features:

• Genomic cline visualization: Generates plots to visualize genomic clines and locus-specific patterns across admixed individuals.
• Integration with BGC and Introgress: Parses and processes output from BGC (Bayesian Genomic Clines) and Introgress for downstream analysis.
• Input generation and filtering: Produces input files including dataset filtering and creation of specialized file formats for cline analyses.
• MCMC output processing: Implements output processing steps such as MCMC thinning and burn-in handling for Bayesian Genomic Clines output.
• Hypothesis testing and interpretation: Provides functions for hypothesis testing and interpretation of genomic clines.
• Post-hoc analysis interfaces: Supports post-hoc analyses through interfaces to ENMeval and RIdeogram.
• Multi-locus differentiation analysis: Analyzes multi-locus differentiation patterns to inform clinal theory and evolutionary inference.

Scientific Applications:

• Assess adaptive processes: Assess intrinsic and extrinsic adaptive processes shaping species boundaries using genomic cline patterns.
• Hybrid zone characterization: Characterize multi-locus differentiation across hybrid zones and locus-specific introgression.
• Test locus-specific introgression: Test hypotheses about locus-specific introgression relative to genome-wide trends.
• Cross-taxa application: Apply genomic cline analyses to both model and non-model organisms.

Methodology:

Processes BGC and Introgress outputs, performs dataset filtering and specialized file-format creation, applies MCMC thinning and burn-in processing, and provides interfaces to ENMeval and RIdeogram.