Single-Sample Germline Variant Filtering for Accurate TMB
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Solution Overview
Problem
Existing methods for variant calling from sequence data struggle to accurately distinguish somatic variants from germline variants without requiring matched normal samples, leading to potential overestimation of tumor mutation burden.
Innovation Solution
A method involving a database filter and a proximity filter is applied to sequence data from a single sample to identify and remove germline variants based on allele count and genomic location, allowing for the distinction between somatic and germline variants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional variant calling methods are used without matched normal samples, then the process is simpler and costs are reduced, but the accuracy of distinguishing somatic variants from germline variants deteriorates
Solution Approach 1:
The patent introduces population frequency data from reference databases as an intermediary to distinguish germline variants. By comparing the variant allele frequency in the tumor sample against the frequency observed in normal population databases, the method can identify germline variants (which appear in both tumor and population databases) without requiring matched normal samples. This intermediary reference data enables accurate variant classification while maintaining the simplified single-sample approach.
2Productivity
If traditional variant calling methods are used without matched normal samples, then the workflow is faster and more efficient, but the reliability of tumor mutation burden estimation deteriorates
Solution Approach 1:
The patent implements a feedback mechanism by iteratively comparing variant allele frequencies against population database frequencies. The method calculates the ratio of tumor variant frequency to population variant frequency, and uses this feedback to classify variants as somatic or germline. This feedback loop enables reliable tumor mutation burden estimation while maintaining workflow efficiency, as it eliminates the need for additional matched normal sample processing steps.
3Measurement precision
If database filtering is applied to remove germline variants, then somatic variant identification becomes more accurate, but the complexity of the variant calling process increases
Solution Approach 1:
The patent simplifies the filtering process by changing the approach from complex multi-step filtering to a straightforward frequency ratio comparison. Instead of applying multiple filtering criteria, the method transforms the problem into comparing a single key parameter: the ratio of tumor variant allele frequency to population variant allele frequency. This parameter transformation maintains high accuracy in somatic variant identification while significantly reducing bioinformatics pipeline complexity.
Data Source
AI summary
Some embodiments of the methods and systems provided herein relate to variant calling from sequence data obtained from a single sample. In some embodiments, a somatic variant can be distinguished from a germline variant based on variant allele frequency in a sample and location in a genome.