MALPACA

MALPACA automates multi-template landmark placement to generate reproducible landmark datasets for quantitative morphological and evolutionary analyses.

Key Features:

• Multiple Template Utilization: Employs multiple templates to accommodate large-scale morphological variation and reduce bias associated with single-template approaches.
• K-means Template Selection: Uses K-means clustering to select representative templates when no prior template information is available.
• Point Cloud Alignment and Correspondence Analysis: Aligns point clouds and performs correspondence analysis across multiple templates to identify landmark positions.
• Improved Accuracy and Consistency: Demonstrates superior accuracy and consistency relative to single-template methods across diverse samples.
• Post-hoc Quality Assessment: Provides per-template post-hoc quality checks to evaluate and refine landmarking results.

Scientific Applications:

• Evolutionary Biology: Facilitates quantitative analyses of morphological phenotypes for evolutionary inference.
• Comparative Morphometrics: Supports landmarking in single- and multi-species studies with significant morphological variability.
• Population and Phenotypic Variation Studies: Enables reproducible landmark datasets for studies of morphological variation among populations or taxa.

Methodology:

Aligns point clouds, performs correspondence analysis using multiple templates, and integrates K-means clustering for template selection.