CNV-BAC

CNV-BAC corrects replication-origin-associated and other sequencing biases in bacterial whole-genome sequencing (WGS) read depth to improve detection of copy number variations (CNVs) in circular bacterial genomes.

Key Features:

• Normalization of Replication Bias: Corrects enrichment of reads near the replication origin caused by circular genome structure and high bacterial replication rates to produce reliable read-depth measurements across the genome.
• Comprehensive Bias Correction: Adjusts for additional known biases in bacterial WGS data beyond replication-origin effects to reduce false positives and false negatives in CNV calling.
• Performance on Simulated and Real Data: Demonstrated improved CNV detection through simulations and analysis of approximately 200 real bacterial WGS samples.

Scientific Applications:

• Microbial genomics: Enables accurate CNV profiling in bacterial genomes for studies of genetic diversity and population genomics.
• Evolution and adaptation studies: Facilitates detection of CNVs involved in evolutionary processes and bacterial adaptation mechanisms.
• Antibiotic resistance research: Identifies copy number changes that may contribute to antibiotic resistance phenotypes.
• Pathogenicity and metabolism investigations: Detects CNVs potentially affecting pathogenicity factors and metabolic capabilities.

Methodology:

Normalizes replication-origin-associated read enrichment and applies additional bias adjustments to WGS read-depth data; validated using simulations and analysis of ~200 bacterial WGS samples.