Genomic Variant Annotation Engine for NGS Data Interpretation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional nucleic acid sequence analysis systems lack user-friendly interfaces and methods to facilitate easy analysis and interpretation of genomic variant candidates, making it difficult to correlate genetic and epigenetic data with clinical relevance.
Innovation Solution
Development of user interfaces and methods for annotating genomic variants, including a system with a mapping engine, variant calling engine, decision support module, and reporter module, which utilize external annotation sources to provide functional and interpretive information, enabling researchers to understand the biological significance of identified variants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If NGS technologies are used to increase sequencing throughput and reduce cost, then more nucleic acid sequences can be analyzed, but the complexity and volume of data requiring interpretation increases significantly
Solution Approach 1:
The patent introduces a computer-implemented system with multiple specialized engines (mapping engine, variant calling engine, annotation engine, interpretation engine) that act as intermediaries between raw NGS data and clinical decision-making. These engines process and transform complex sequencing data into annotated and interpreted results, resolving the contradiction by managing data analysis complexity while maintaining high sequencing throughput.
Solution Approach 2:
The data analysis process is segmented into distinct functional modules: mapping sequences to reference genomes, calling variants, annotating variants with functional information, and interpreting clinical significance. This segmentation allows each module to handle specific aspects of the complex data processing task independently, making the overall system more manageable and scalable.
2Loss of information
If comprehensive annotation and interpretation of genomic variants is performed, then biological and clinical significance is better determined, but computational resources and time are increased
Solution Approach 1:
The annotation engine pre-populates variant records with functional annotations from multiple databases (e.g., gene function, protein impact, regulatory elements) before clinical interpretation is needed. This preliminary annotation process ensures that when variants require clinical interpretation, the biological information is already organized and available, reducing the time required for comprehensive analysis.
Solution Approach 2:
The system incorporates feedback mechanisms where interpretation results and user interactions inform subsequent annotation and analysis processes. The system learns from interpretation outcomes to optimize future annotation priorities, balancing information completeness with analysis efficiency by focusing computational resources on variants with higher clinical relevance.
Data Source
AI summary
Systems and method for annotating variants within a genome can call variants from reads or receive called variants directly and associate the called variants with functional annotations and interpretive annotations. A summary report of the called variants, the associated functional annotations, and the associated interpretive annotations can be generated.