hapLOHseq

hapLOHseq detects regions of allelic imbalance (AI) in next-generation sequencing data to identify somatic AI in samples with low tumor cellularity or subclonal populations.

Key Features:

• Detection Sensitivity: Detects AI events spanning 10 megabases or greater in exome sequencing with detection at ~16% sample representation at 80× coverage and at ~4% representation in whole genome sequencing at 30× coverage, with sensitivity exceeding existing software.
• Application to Cancer Research: Identifies AI regions associated with tumor subclones and low-cellularity samples to support analyses of disease progression and treatment-related genomic changes.
• Performance Validation: Demonstrated superior performance detecting large chromosomal changes across pancreatic samples from The Cancer Genome Atlas (TCGA).

Scientific Applications:

• Early Cancer Detection: Detects AI in low tumor-cellularity samples to enable identification of tumor-derived genomic alterations at early stages.
• Prognostic Assessment: Detects subtle genomic changes that can inform prognostic evaluation of disease progression.
• Therapeutic Selection: Reveals AI regions associated with specific tumor subclones to inform selection of targeted therapies.

Methodology:

Operates on next-generation sequencing data using an algorithm optimized for high sensitivity and specificity to detect allelic imbalance events present in minority cell populations within heterogeneous samples.