DNA Sequence Analysis System for Genome Variant Detection
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Solution Overview
Problem
Current tools for analyzing next-generation sequencing (NGS) data are limited in detecting structural variants (SVs) and are slow, often finding only subsets of variants, failing to combine all available evidence from single or multiple samples.
Innovation Solution
A computer-based DNA sequence analysis system that receives DNA sequencing data and reference sequences, analyzing multiple data types to identify all types of variants, including SNVs, indels, deletions, duplications, inversions, translocations, and copy number changes, using a joint analysis of distinct data type outputs for faster and more accurate detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If current variant finding pipelines are used to detect structural variants, then detection can be performed, but the analysis is slow and takes a long time to run on single or multiple samples
Solution Approach 1:
The patent segments the genome into multiple bins and processes each bin independently using a divide-and-conquer approach. This allows parallel processing of different genomic regions, significantly reducing the overall analysis time while maintaining comprehensive coverage of all variants.
Solution Approach 2:
The patent performs preliminary filtering and preprocessing of sequencing reads before main variant detection. By pre-processing the data (filtering low-quality reads, pre-aligning sequences), the system reduces the computational burden during the main detection phase, thereby speeding up the overall process.
2Reliability
If multiple variant finders are employed to detect all types of variants, then comprehensive variant detection is achieved, but divergent sets of predictions are produced and complexity increases
Solution Approach 1:
The patent implements a universal variant detection system that can detect all types of variants (SNVs, indels, structural variants) through a single integrated pipeline. The system uses a unified statistical framework that handles different variant types consistently, eliminating the need for multiple specialized tools and their associated complexity.
Solution Approach 2:
The patent merges multiple sources of evidence (read depth, split reads, discordant pairs, assembly-based evidence) into a unified variant detection framework. By combining these different evidence types within a single statistical model, the system achieves comprehensive detection without producing divergent predictions from separate tools.
3Reliability
If current variant finding pipelines are used, then some variants can be detected, but none of the pipelines combine all available evidence from single or multiple samples for detecting all variant types
Solution Approach 1:
The patent extends variant detection from single-sample analysis to multi-sample joint analysis by adding a population dimension. The system simultaneously analyzes multiple samples, leveraging shared genetic information across individuals to improve variant detection sensitivity and accuracy, particularly for rare variants.
Solution Approach 2:
The patent introduces a probabilistic graphical model as an intermediary framework that integrates multiple evidence types and multiple samples. This statistical model acts as a mediator that combines diverse data sources (different variant types, multiple samples) into a unified inference process, achieving comprehensive evidence integration.
Data Source
AI summary
The present disclosure generally relates to finding genome rearrangements from sequencing data. DNA sequence analysis systems and methods directed to identifying all sequence variants in a genome are described herein. Such systems and methods demonstrate distinct and improved features relating to the accuracy and speed with which all sequence variants in a genome are identified.