Known-Allele Read Mapping with DAG-Guided Alignment
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Solution Overview
Problem
Existing methods for analyzing next-generation sequencing (NGS) reads lack mathematical precision and fail to utilize available genomic context, often aligning reads to arbitrary references, leading to computational inefficiencies and limited information use.
Innovation Solution
Utilizing a directed acyclic graph (DAG) that represents multiple alternative sequences at known locations, excluding incongruent mappings, and employing mathematically robust alignment algorithms like Smith-Waterman to align reads, thereby improving computational efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If reads are mapped to a comprehensive reference genome using traditional alignment algorithms, then mapping completeness is improved, but computational time and processing resources increase significantly
Solution Approach 1:
The patent pre-processes the reference genome to identify and mark known variant positions (SNPs, indels, structural variants) before read mapping. This preliminary annotation allows the aligner to skip exhaustive comparisons at these positions, using the pre-identified variants to guide alignment decisions and reduce computational search space while maintaining mapping accuracy
Solution Approach 2:
The reference genome is segmented into regions with known variants and regions without. The aligner processes these segments differently: using efficient variant-aware algorithms for variant regions and standard alignment for non-variant regions, thereby optimizing computational resources based on regional characteristics
2Measurement precision
If traditional alignment algorithms are used to map NGS reads, then mathematical precision is improved, but computational complexity and processing difficulty increase
Solution Approach 1:
The patent changes the parameters of the alignment problem by incorporating known variant information as constraints. Instead of searching all possible alignments, the algorithm uses variant positions to define restricted search spaces, changing the alignment parameters from exhaustive comparison to constrained optimization, thereby reducing computational complexity while preserving accuracy through mathematically robust algorithms like Smith-Waterman applied selectively
3Productivity
If reads are mapped to an arbitrary reference genome, then mapping speed is improved, but information completeness and genomic context are lost
Solution Approach 1:
The patent introduces an intermediary layer between the read and reference genome: a variant annotation layer that provides genomic context information. This intermediary structure contains pre-identified variants and their contextual information, allowing the aligner to rapidly match reads to appropriate reference versions while preserving access to comprehensive genomic context, thus maintaining both speed and information completeness
Data Source
AI summary
The invention generally relates to genomic studies and specifically to improved methods for read mapping using identified nucleotides at known locations. The invention provides methods of using identified nucleotides at known places in a genome to guide the analysis of sequence reads from that genome by excluding potential mappings or assemblies that are not congruent with the identified nucleotides. Information about a plurality of SNPs in the subject's genome is used to identify candidate paths through a genomic directed acyclic graph (DAG). Sequence reads are mapped to the candidate paths.