Tandem Repeat Mapping With Refined Markov Models
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Solution Overview
Problem
Sequencing of long stretches of repeated nucleotides is difficult due to the high variability and instability of tandem repeats, making it challenging to accurately map sequence reads to genomic regions associated with diseases such as Huntington's disease and fragile X syndrome.
Innovation Solution
The use of repeat definitions and Markov models to generate graphs and refine models for mapping sequence reads, allowing for accurate segmentation and mapping of reads to genomic regions with tandem repeats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sequence reads are mapped to genomic regions with tandem repeats using conventional methods, then mapping can be performed, but mapping accuracy deteriorates due to high variability and instability of tandem repeats
Solution Approach 1:
The patent segments the mapping process into multiple steps: first identifying tandem repeat regions using repeat definitions, then separately analyzing sequence reads within these regions using specialized algorithms. This segmentation allows different mapping strategies to be applied to different genomic regions, improving overall mapping accuracy while managing the complexity of tandem repeat regions.
Solution Approach 2:
The patent introduces repeat definitions and Markov models as intermediary tools between the sequence reads and the genomic reference. These intermediaries capture the variability characteristics of tandem repeats and enable accurate mapping by accounting for expansions and contractions that would otherwise cause mapping failures.
2Adaptability or versatility
If the number of possible mappings is increased to account for genomic expansions, then mapping completeness improves, but computational complexity increases exponentially
Solution Approach 1:
The patent employs dynamic programming algorithms that efficiently explore the space of possible mappings without exhaustively enumerating all possibilities. The algorithm dynamically adjusts the search based on observed sequence characteristics, maintaining mapping completeness while avoiding exponential computational complexity through intelligent pruning and optimization.
Solution Approach 2:
The patent changes the parameter space by using repeat definitions that specify expected repeat unit sequences and lengths. This transforms the mapping problem from one requiring enumeration of all possible repeat counts to one where repeat parameters can be estimated directly from sequence data, dramatically reducing computational complexity while maintaining adaptability.
3Productivity
If conventional mapping methods are used on tandem repeat regions, then processing speed is maintained, but measurement precision of repeat counts deteriorates
Solution Approach 1:
The patent performs preliminary identification and characterization of tandem repeat regions before attempting to map sequence reads. By pre-defining repeat units, interruption sequences, and expected variations, the system prepares the necessary framework in advance, enabling both rapid processing and accurate repeat count measurement without requiring slow, exhaustive analysis during the main mapping phase.
Data Source
AI summary
Systems and methods for mapping a plurality of sequence reads to a genomic region are provided. A plurality of sequence reads mappable to the genomic region are obtained. An initial Markov model for the genomic region is obtained. The initial Markov model comprises at least (i) a first repeat for a first repeat region, (ii) a second repeat for a second repeat region, and (iii) an intermediate region linking the first repeat to the second repeat. The initial Markov model is refined using the plurality of sequence reads, thereby obtaining a refined Markov model. For each respective sequence read in the plurality of sequences, the respective sequence read is used to find a highest probability path through the Markov model. This highest probability path is then used to map the respective sequence read to the genomic region.