shallowHRD

shallowHRD assesses homologous recombination deficiency (HRD) in tumors using shallow whole genome sequencing (sWGS) at approximately 0.4x–1x coverage to detect large-scale genomic alterations associated with HRD status.

Key Features:

• Low-Coverage Sequencing: Uses shallow whole genome sequencing (sWGS) data at approximately 0.4x–1x coverage to infer HRD status.
• Genomic Segmentation Analysis: Performs segmentation of tumor genomic profiles to identify large-scale genomic alterations (LGAs), analogous to Large-scale State Transitions (LSTs), without reliance on ploidy or absolute copy number metrics.
• Performance Metrics: Reports HRD detection performance with 87.5% sensitivity and 90.5% specificity.
• Predictive Utility: Enables prediction of tumor response to poly(ADP-ribose) polymerase (PARP) inhibitors based on detected HRD-associated alterations.
• Low Data Footprint: Operates on low-coverage sWGS outputs producing small data footprints compared with high-coverage approaches.

Scientific Applications:

• Clinical Research: Supports prediction of therapeutic response to PARP inhibitors in HRD-positive tumors.
• Tumor Profiling: Applicable to profiling HRD status in breast, ovarian, pancreatic, and prostate tumors.
• Fixed Tissue Analysis: Compatible with analysis of fixed-formalin paraffin embedded tissues.

Methodology:

Implemented as an R script executable from the command line, shallowHRD processes normalized read count data from sWGS segmented into sliding windows across the genome and was developed using ControlFREEC output while remaining adaptable to similar software platforms.