Mutational Signature Analysis Segmentation
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Solution Overview
Problem
Current methods for identifying mutational signatures in DNA samples are limited by the large number of signatures and the challenge of distinguishing between common and rare signatures, which affects their practical application in characterizing cancer genomes.
Innovation Solution
The method involves analyzing large cohorts of whole-genome sequencing (WGS) tumors to identify mutational signatures. By separating signatures into common and rare categories, the approach focuses on fitting common signatures first and then adding rare signatures based on improved fit, thereby enhancing the accuracy of mutational signature analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If all mutational signatures are analyzed simultaneously, then comprehensive coverage is achieved, but computational complexity and difficulty of detection increase
Solution Approach 1:
The patent segments the large set of mutational signatures into two distinct groups: a first set of common signatures and a second set of rare signatures. This segmentation allows the analysis to be divided into manageable stages - first fitting common signatures to establish a baseline, then selectively fitting rare signatures only when necessary to explain residual mutations. This resolves the contradiction by reducing computational complexity while maintaining comprehensive coverage through a systematic two-stage approach.
Solution Approach 2:
The patent performs preliminary action by first fitting the first set of common mutational signatures to the sample data before attempting to fit rare signatures. This preliminary fitting establishes a foundation that explains the majority of mutational patterns, and only the residual unexplained mutations are then subjected to analysis for rare signatures. This preliminary action reduces the computational burden while ensuring comprehensive analysis is not compromised.
2Measurement precision
If all mutational signatures are fitted to maximize accuracy, then measurement precision improves, but loss of time increases
Solution Approach 1:
By segmenting signatures into common and rare sets, the patent implements a time-efficient two-stage fitting process. The first stage quickly identifies common signatures that explain the majority of mutations, providing immediate accurate results. The second stage only processes rare signatures when needed, avoiding unnecessary computational time while maintaining high measurement precision for both common and rare signature identification.
Solution Approach 2:
The patent applies partial action by selectively fitting rare signatures only when the residual mutations after common signature fitting indicate their presence. This avoids the excessive action of fitting all rare signatures to every sample, which would waste time on samples where rare signatures are not relevant. The partial fitting approach maintains measurement precision by only analyzing rare signatures when they are actually needed to explain the data.
Data Source
AI summary
The invention provides a method of characterising a DNA sample, the method including the steps of: obtaining a mutational catalogue for the sample, wherein a mutational catalogue comprises counts of mutations in a plurality of predetermined categories; obtaining a mutational signatures catalogue comprising a first set of one or more mutational signatures and a second set of one or more mutational signatures; determining a first set of exposures of the sample to the mutational signatures in the first set of mutational signatures; identifying at least one of the mutational signatures in the second set of mutational signatures that is likely to be present in the sample using the results of the determining; and providing an indication of which of the mutational signatures in the mutational signatures catalogue is present in the sample. Methods of providing a mutational signature catalogue, and related systems and products are also described.


