Cluster segmentation and conditional base calling
By segmenting clusters into subpopulations based on specific conditions and using a Gaussian mixture model for base calling, the variation in inter-cluster intensity profiles is minimized, reducing errors and enhancing sequencing run efficiency.
JP2025532443APending Publication Date: 2025-10-01ILLUMINA INC
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Patent Information
- Application Number
- JP2024557195
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2022-09-16
- Filing Date
- 2023-09-15
- Publication Date
- 2025-10-01
AI Technical Summary
Technical Problem
The variation in inter-cluster intensity profiles during sequencing runs leads to decreased data throughput and increased error rates in base calling due to factors such as fragment length distribution, phase shifts, bleaching, cluster size, overlapping colonies, uneven illumination, and impurities on the flow cell.
Method used
Segmenting clusters into subpopulations based on specific conditions and performing base calling separately for each subpopulation using a Gaussian mixture model to minimize inter-cluster intensity variation.
Benefits of technology
This approach reduces base calling errors and improves throughput by ensuring clusters with similar conditions are grouped together, allowing for accurate fitting and base calling within each subpopulation.
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Abstract
The disclosed technology is directed to cluster segmentation and base calling. The disclosed technology describes a computer-implemented method that includes segmenting a population of clusters into multiple subpopulations of clusters based on one or more previous bases called in one or more previous sequencing cycles of a sequencing run. In a current sequencing cycle of the sequencing run, the method includes applying a mixture of four distributions to current sequenced data of each subpopulation of clusters in the multiple subpopulations of clusters, the four distributions corresponding to the four bases adenine (A), cytosine (C), guanine (G), and thymine (T), and the current sequenced data generated in the current sequencing cycle. The method further includes base calling a cluster within a particular subpopulation of clusters using a corresponding mixture of the four distributions.
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