NCBI-taxonomist

NCBI-taxonomist manages and links taxonomic data from NCBI to integrate related metadata across Entrez databases for applications such as metagenomic analyses.

Key Features:

• Implementation: Implemented in Python 3 (>=3.8).
• Command set: Six commands (map, collect, extract, resolve, import, group) that facilitate construction of analytical pipelines for taxonomic data processing.
• Database independence: Operates without requiring pre-downloaded taxonomic databases and supports local storage of retrieved taxonomic data.
• Entrez linkage: Links taxonomic records to related metadata in other Entrez databases.
• Cross-database compatibility: Works with taxonomic information used across various life sciences databases to enable cross-database linkage.

Scientific Applications:

• Metagenomic data integration: Maps taxonomic identifiers to link sequencing datasets with metadata in Entrez for metagenomic analyses.
• Metadata enrichment: Resolves and imports taxonomic information to augment biological datasets and associate related records across databases.
• Analytical workflow assembly: Enables extraction, grouping, and resolution of taxonomic data within custom analytical pipelines.

Methodology:

Implements six explicit commands (map, collect, extract, resolve, import, group) in Python 3 (>=3.8) to fetch taxonomic data from NCBI, link records to Entrez metadata, and store or group entries locally.