Keanu

Keanu visualizes taxonomic composition and organismal abundance in metagenomic datasets by analyzing BLAST alignment outputs against an NCBI Taxonomy-derived database.

Key Features:

• Visualization types: Generates collapsible trees and bilevel partition graphs where node and arc sizes indicate organismal abundance.
• BLAST-based input processing: Accepts BLAST query results with taxon IDs per line and processes them via format_input.py.
• Taxonomy database construction: Builds taxonomy.dat and merged_deleted.dat from names.dmp, nodes.dmp, delnodes.dmp, and merged.dmp using create_databases.py.
• BLAST alignment analysis: Analyzes sequence alignments against a BLAST database to derive taxonomic hits for visualization.
• Implementation: Implemented in Python as a command-line application.

Scientific Applications:

• Shotgun metagenomics biodiversity profiling: Visualizes taxonomic composition and relative abundance from shotgun metagenomic samples.
• Environmental and paleoecological investigation: Supports analysis of environmental samples such as bluff paleosols (interior Alaska) and visualization of taxonomic hits used to investigate origins of structures like a krotovina.

Methodology:

Processes BLAST query results with taxon IDs via format_input.py; creates taxonomy.dat and merged_deleted.dat from names.dmp, nodes.dmp, delnodes.dmp, and merged.dmp using create_databases.py (NCBI Taxonomy files); analyzes BLAST alignments against a BLAST database and generates collapsible tree and bilevel partition graph visualizations with node/arc sizes representing abundance.