Metacoder

Metacoder parses, manipulates, and visualizes hierarchical taxonomic data from metabarcoding studies to enable quantitative analysis of community-level biodiversity.

Key Features:

• Hierarchical Data Parsing: Parses various text-based formats containing taxonomic classifications, taxon names, identifiers, or sequence identifiers.
• Manipulation Functions: Provides functions to subset, sample, and order parsed hierarchical data while preserving parent–child relationships.
• Flexible Tree-Based Visualization: Plots tree-format visualizations that can represent up to four arbitrary statistics simultaneously by mapping statistics to node and edge color and size.
• Primer-Bias Exploration via Digital PCR: Integrates digital PCR functions to explore barcode primer bias in metabarcoding datasets.
• Applicability to Arbitrary Hierarchical Data: Applies to hierarchical datasets beyond taxonomy, including gene ontology and geographic location data.

Scientific Applications:

• Community Ecology and Biodiversity Analysis: Quantifies and visualizes taxonomic composition and diversity in community-level metabarcoding studies.
• Primer Bias Assessment: Evaluates primer amplification bias in metabarcoding workflows using integrated digital PCR analyses.
• Hierarchical Data Analysis Outside Taxonomy: Analyzes other hierarchical datasets such as gene ontology annotations and geographic hierarchies.

Methodology:

Implements a dynamic parsing system for diverse text-based taxonomic inputs, hierarchical-aware functions to subset, sample, and order data, and plotting routines that map up to four statistics to node and edge color and size within a tree format.