Non-acyclic Genome Graph Alignment on Heterogeneous Systems

The patent segments the non-acyclic genome graph into multiple acyclic subgraphs (DAGs) by identifying and removing cyclic regions. Each subgraph can be processed independently using efficient DAG-based alignment algorithms, thereby maintaining alignment accuracy while reducing computational complexity. The segmentation allows the system to handle complex genomic variations without the full computational burden of processing the entire non-acyclic graph at once.

The patent performs preliminary actions by pre-processing the genome graph to identify cyclic regions and prepare acyclic subgraphs before the actual alignment process. This includes building indexes for the acyclic portions and pre-computing alignment parameters, which reduces the computational load during the main alignment phase and improves overall processing efficiency while maintaining accuracy.

The patent divides the fine-grained non-acyclic graph into multiple acyclic subgraphs, allowing parallel processing of alignment tasks. Each subgraph can be aligned independently and simultaneously, which maintains the high precision benefits of fine-grained representation while significantly reducing total execution time through parallel computation.

The patent applies partial action by focusing computational resources on aligning reads to specific acyclic subgraphs that are most relevant to the query sequences. Rather than exhaustively processing the entire graph with equal intensity, the method selectively processes portions of the graph that provide the most value for alignment precision, thereby reducing overall execution time while maintaining high precision where needed.

The patent segments the genome graph into acyclic subgraphs, which can be processed using memory-efficient DAG-based alignment algorithms. This segmentation allows exact alignment to be performed on smaller, manageable portions of the graph, reducing the peak memory requirements compared to processing the entire non-acyclic graph with exact alignment algorithms.

The patent creates simplified copies or representations of the acyclic subgraphs that are optimized for memory-efficient processing. These copies contain only the necessary information for alignment tasks, allowing exact alignment algorithms to run with reduced memory footprints while maintaining alignment quality.

The patent segments the non-acyclic graph into acyclic subgraphs that preserve the original graph's structural information and alignment properties. By carefully identifying boundaries between cyclic and acyclic regions, the segmentation maintains alignment quality at the subgraph level while enabling efficient DAG-based processing, thus avoiding the quality degradation associated with forced DAG-ification of the entire graph.

The patent applies different processing strategies to different parts of the graph: acyclic subgraphs are processed using efficient DAG-based algorithms, while cyclic regions are handled with specialized approaches that preserve alignment quality. This local quality approach ensures that each region is processed with the most appropriate method, maintaining overall alignment quality while improving processing efficiency.