Chanjo

Chanjo performs coverage analysis of massive parallel sequencing (MPS) data to annotate per-region coverage and completeness and to aggregate sample-level coverage for clinical whole exome and genome sequencing.

Key Features:

• Persistent Storage and Aggregation: Stores coverage from thousands of samples in an SQL database to enable aggregate queries and identification of problematic genomic regions.
• Coverage Annotation with Sambamba and BED: Annotates coverage and completeness using Sambamba with general BED files.
• File Format Support: Accepts BAM and BED file formats for input and analysis.
• Customized Reporting: Produces structured and dynamic coverage reports via the Chanjo Report component with PDF output filtered by regions, coverage thresholds, or sample subsets.
• Pipeline Integration and Automation: Designed for integration into UNIX-style pipelines to enable automated, persistent coverage analysis.

Scientific Applications:

• Coverage quality control: Identification of poorly covered genomic regions and potential false negatives or false positives within regions of interest.
• Aggregate and longitudinal analysis: Detection of systematic coverage gaps across multiple samples or sequencing methods through aggregated queries.
• Clinical research and diagnostics reporting: Generation of per-region and per-sample coverage reports to support clinical sequencing workflows and diagnostic assessment.

Methodology:

Implemented in Python; annotates coverage using Sambamba with BED files; ingests BAM inputs; stores sample-level coverage in an SQL database for aggregate queries; generates reports via Chanjo Report with PDF outputs; supports whole exome and genome sequencing and integration into UNIX-style pipelines.