BoaG

BoaG analyzes NCBI's non-redundant (NR) protein sequence database to support large-scale genomic analyses of protein sequence diversity, taxonomic origin, and functional annotation.

Key Features:

• Domain-Specific Language: A domain-specific language tailored for genomics that enables precise queries and analyses against NCBI's NR protein database.
• Shared Data Science Infrastructure: A shared infrastructure that aggregates NR-derived datasets and supports collaborative computational analyses.
• CD-HIT Clustering: Incorporates CD-HIT clustering to organize protein sequences at various sequence similarity levels.
• Efficient Query Performance: Processes large NR datasets efficiently to compute metrics such as average protein sequence length and to retrieve common taxonomic assignments and functional annotations.
• Annotation Redundancy Analysis: Leverages clustering information to identify annotation redundancy in NR, including reported redundancy at the 95% sequence similarity level.

Scientific Applications:

• Taxonomic Origin Identification: Determine the taxonomic origin of protein sequences within NCBI's NR database.
• Functional Annotation Exploration: Explore and summarize functional annotations associated with NR protein sequences.
• Data Quality and Redundancy Assessment: Assess data quality by quantifying annotation redundancy in NR.

Methodology:

Integrates protein sequence data, functional annotations, and taxonomic assignments from the NR database and applies CD-HIT clustering to manage sequence similarity levels, enabling efficient querying and analysis of large datasets.