CoV-Seq

CoV-Seq analyzes SARS-CoV-2 genome sequences to predict gene boundaries and identify genetic variants for genomic surveillance and research.

Key Features:

• Automated analysis: Automatically predicts gene boundaries and identifies genetic variants in SARS-CoV-2 sequences.
• Aggregated datasets: Aggregates publicly available SARS-CoV-2 sequences from GISAID, NCBI, EMBL (European Nucleotide Archive), and CNGB and extracts genetic variants.
• High-throughput processing: Supports batch processing of sequences for large-scale analyses.
• Implementation: Implemented using Python and JavaScript.

Scientific Applications:

• Viral evolution: Studying SARS-CoV-2 evolution by identifying and cataloging genetic variants.
• Mutation tracking: Monitoring mutation occurrence and emergence of variant sites across genomes.
• Epidemiological investigations: Informing transmission and outbreak analyses using genomic variation data.
• Population-scale genomics: Enabling comparative and large-scale analyses across aggregated SARS-CoV-2 datasets.

Methodology:

Aggregates publicly available SARS-CoV-2 sequences from GISAID, NCBI, EMBL (European Nucleotide Archive), and CNGB, and automatically predicts gene boundaries and identifies genetic variants; implemented in Python and JavaScript.