Sequencing-Based Genotyping for Structural Variant Allele Calling
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Solution Overview
Problem
Current computational tools are unable to accurately perform allelic decomposition of genes with structural alterations, particularly those with multiple copies or highly homologous pseudogenes, which is crucial for genotyping ADME genes to optimize drug treatment and dosage decisions.
Innovation Solution
A method and system for genotyping genes using high-throughput sequencing data that aligns reads to a reference genome, identifies nucleic acid and structural variants, detects gene-disrupting mutations, and selects star-alleles with penalty scoring to refine genotypes, capable of handling structural rearrangements and non-uniform coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current computational tools are used for allelic decomposition, then analysis speed is maintained, but accuracy is insufficient for genes with structural alterations and multiple copies
Solution Approach 1:
The patent segments the genotyping process into distinct computational stages: read alignment to reference genome, variant identification (SNPs, indels, structural variants), copy number estimation, and genotype calling. This segmentation allows each stage to be optimized independently, improving overall accuracy while managing computational complexity through modular processing of highly polymorphic genes with multiple copies and pseudogenes
Solution Approach 2:
The patent introduces intermediate computational structures including alignment scores, variant call formats, and copy number estimates as mediators between raw sequencing data and final genotype calls. These intermediaries enable complex allelic decomposition by breaking down the computational task into manageable steps that can handle structural alterations and homologous pseudogenes
2Adaptability or versatility
If array-based genotyping assays are used, then cost is reduced, but coverage scope and accuracy are limited
Solution Approach 1:
The patent implements a universal computational framework that processes high-throughput sequencing data across diverse gene types including ADME genes, highly polymorphic genes, genes with structural alterations, and genes with multiple copies. This multi-functional approach simultaneously achieves broad gene coverage and high genotyping accuracy by adapting the same core algorithm to different gene characteristics
3Loss of information
If existing copy number phasing tools are used, then copy number detection is achieved, but exact sequence content reconstruction is not possible
Solution Approach 1:
The patent performs preliminary actions by first estimating copy number from read depth data, then using this information to guide subsequent variant identification and genotype calling. This preliminary copy number estimation enables the algorithm to reconstruct exact sequence content by knowing how many copies of each allele to expect, thereby reducing information loss while managing complexity through staged processing
Data Source
AI summary
Described herein are methods and systems for predicting the genotype of one or more genes utilizing high throughput sequencing data. The provided methods and systems allow for accurate genotyping of genes, including ADME genes, and can be used to identify novel alleles.