Genesis-indel

Genesis-indel analyzes unmapped reads from Next Generation Sequencing (NGS) data to identify novel insertions and deletions (indels) that are overlooked by standard alignment-based variant calling.

Key Features:

• Unmapped-read targeting: Specifically analyzes reads that remain unmapped after short-read alignment to recover variants excluded from standard workflows.
• Novel indel discovery: Identified 72,997 novel high-quality indels in a study of 30 breast cancer patients from The Cancer Genome Atlas (TCGA).
• Unannotated variant detection: Detected 16,141 indels that were not present in widely used mutation databases.
• Enrichment in cancer genes: Statistical analysis demonstrated significant enrichment of the discovered indels within oncogenes and tumor suppressor genes.
• Functional annotation and pathway association: Functional annotation linked identified indels to cancer-associated pathways and indicated high to moderate predicted impacts on protein function.
• Rescue of hidden indels: Recovers indels overlapping genes that lacked indel calls in the originally mapped reads, providing additional mutation discovery.
• Conservation across subtypes: Found that unmapped reads were conserved across different breast cancer subtypes, implicating potential relevance to subtype divergence.

Scientific Applications:

• Cancer variant discovery: Expand variant catalogs in cancer genomics by recovering indels missed by alignment-based workflows.
• Breast cancer subtype analysis: Investigate subtype divergence by analyzing conserved unmapped reads from TCGA breast cancer samples.
• Functional impact assessment: Link novel indels to cancer-related pathways and predicted effects on protein function for mechanistic studies.
• Database curation: Contribute previously unannotated indels to mutation databases and variant resources.
• Complementary analysis: Supplement standard NGS variant calling pipelines by re-evaluating unmapped reads to increase depth and accuracy of indel discovery.

Methodology:

Genesis-indel analyzes unmapped NGS reads to identify insertions and deletions, performs statistical enrichment analyses for oncogenes and tumor suppressor genes, and carries out functional annotation linking indels to cancer-associated pathways and predicted impacts on protein function.