FORGe

FORGe ranks genetic variants and optimizes graph-based reference genomes to improve sequencing read alignment and reduce allelic bias.

Key Features:

• Variant ranking: Ranks genetic variants based on their potential impact on the reference genome's structure and utility.
• Graph construction: Integrates genetic variants into the linear reference genome to construct a graph genome that includes alternative sequences.
• Alignment improvement: Improves sequencing read alignment accuracy by eliminating penalties associated with mismatches between reads and the reference.
• Trade-off modeling: Models trade-offs between alignment accuracy and computational overhead, including increased reference ambiguity and genome index storage and query costs.
• Variant prioritization: Provides a systematic method for prioritizing which variants to include in the graph to balance alignment gains against computational costs.

Scientific Applications:

• Genomics research: Enables more accurate variant-aware analyses and read alignments in genomic studies.
• Personalized medicine: Facilitates detection of individual-specific variants to support personalized diagnostics and targeted therapies.
• Population genetics: Supports analysis of genetic diversity and allele frequency by incorporating population variants into reference graphs.
• Disease variant discovery: Improves identification of disease-associated mutations by reducing reference-induced alignment errors.

Methodology:

Computational steps explicitly include ranking variants by potential impact, integrating selected variants into a graph genome representing alternative sequences, and modeling trade-offs between alignment accuracy and computational overhead such as reference ambiguity and genome index storage and query costs.