Genotype Analysis Method for Causative Variant Prioritization
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Solution Overview
Problem
Genomic sequencing generates vast amounts of data that are difficult to navigate without assumptions and filters, which can lead to inaccurate assessments by either excluding important information or including too much data, impeding the parsing of sequencing data.
Innovation Solution
A computer-implemented method that ranks genotypes based on association scores and inheritance pattern scores, allowing for the consideration of variants that do not conform to expected patterns, facilitating causative variant discovery, diagnosis, and determining inheritance patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If assumptions and filters are applied to minimize sequencing data, then data navigation becomes easier, but important information may be excluded leading to inaccurate assessments
Solution Approach 1:
The patent implements dynamic filtering where the stringency of inheritance pattern filters is adjusted based on user input and analysis context. The system allows users to specify whether to apply strict Mendelian inheritance filters or more permissive filters that accommodate non-Mendelian patterns, enabling the filtering mechanism to adapt to different analytical needs rather than applying a fixed filter set
Solution Approach 2:
The patent segments the filtering process into multiple independent stages: initial data processing, inheritance pattern analysis, and final variant prioritization. Each stage applies appropriate filters selectively, allowing important information to be preserved in early stages while noise is reduced in later stages, thus maintaining both ease of navigation and assessment accuracy
2Reliability
If no assumptions and filters are applied to sequencing data, then all information is retained for accurate assessment, but data parsing becomes impeded due to overwhelming volume
Solution Approach 1:
The patent performs preliminary inheritance pattern analysis on all sequencing data before final variant prioritization. By pre-processing the data to identify and score potential inheritance patterns, the system reduces the complexity of subsequent parsing while retaining all important information, as the preliminary analysis creates an organized framework that guides further analysis without excluding potential variants
3Productivity
If strict inheritance pattern filters are applied, then prioritization of conforming variants is improved, but variants that do not conform to expected patterns are excluded
Solution Approach 1:
The patent changes the parameter of filter stringency by offering multiple inheritance pattern filter options (strict Mendelian, relaxed Mendelian, non-Mendelian). Users can select the appropriate filter level based on the specific clinical scenario and family pedigree characteristics, allowing the system to maintain high prioritization efficiency for common patterns while remaining adaptable to discover rare non-conforming variants when needed
Data Source
AI summary
The disclosure provides methods and systems for analyzing genotype data. In some embodiments, a computer-implemented method comprises receiving data relating to one or more phenotypes of a subject or family members thereof, and ranking genes based on their association score with one or more phenotypes. Next, an output of the data is generated, the output comprising a comparison of the data based on the association score. The comparison can be in at least one of numeric and graphic form.