PaCBAM

PaCBAM computes depth of coverage and allele-specific pileup statistics from whole-exome and targeted next-generation sequencing (NGS) data to characterize genomic regions and single-nucleotide positions for downstream analysis.

Key Features:

• Depth of Coverage and Allele-Specific Pileup Statistics: Computes detailed per-region and per-position depth and allele-specific pileup metrics for variant and coverage assessment.
• Multi-Core Computational Engine: Implements parallel processing across multiple CPU cores to accelerate analysis of large sequencing datasets.
• On-the-Fly Read Duplicates Filtering: Performs duplicate read filtering during processing to reduce redundant counts without a separate post-processing step.
• Comprehensive Output: Produces text output files and visual reports summarizing coverage and allele-specific statistics for downstream interpretation.

Scientific Applications:

• Precision Medicine: Provides allele-level and coverage metrics applicable to clinical and translational studies requiring accurate characterization of targeted regions and single-nucleotide positions.
• Large Cohort Studies: Supports scalable interrogation of large cohorts by reducing processing time and memory usage through parallel computation and on-the-fly filtering.

Methodology:

Implemented in C, PaCBAM uses a multi-core parallel computational engine, computes depth-of-coverage and allele-specific pileup statistics, applies on-the-fly read duplicate filtering, and generates text outputs and visual reports.