A Method and System for Evaluating DNA Storage Sequencing Depth Based on Channel Simulation

By using channel simulation and a log-normal distribution model, the problem of inaccurate sequencing coverage depth prediction in DNA storage was solved, enabling more accurate sequencing coverage depth calculation, reducing costs and improving decoding success rate.

CN122090902APending Publication Date: 2026-05-26TIANJIN UNIV SYNTHETIC BIOLOGY FRONTIER RES INST
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Patent Information

Application Number
CN202610042156.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-13
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies are inaccurate in predicting sequencing coverage depth in DNA storage, which cannot effectively guide real-world experiments, resulting in incomplete data recovery or wasted costs.

Method used

We employ a log-normal distribution model based on channel simulation, fit the channel probability distribution parameters through maximum likelihood estimation, and combine coupon collection problems and combinatorial mathematical methods to calculate the sequencing coverage depth boundary in noise-free and noisy channels.

Benefits of technology

It provides more accurate sequencing coverage depth prediction, reduces the cost of reading DNA storage data, increases the success rate of decoding, reduces reagent waste, and enhances system reliability.

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Abstract

This invention discloses a method and system for evaluating DNA storage sequencing depth based on channel simulation, addressing the problems of inaccurate predictions and limited guidance in existing uniform distribution models. The method includes: when sequencing data is available, fitting real data to obtain log-normal distribution parameters μ and σ; when sequencing data is unavailable, obtaining μ and σ through simulation modeling based on experimental parameters; and combining these parameters to calculate the decoding ratio of the coding strand in the noiseless channel and the sequencing depth boundary in the noisy channel. The system includes input, storage channel modeling, sequencing depth calculation, and output modules. The model of this invention closely reflects reality, provides accurate predictions, reduces DNA storage and retrieval costs, improves the success rate of single-sequencing decoding, and is easy to use, facilitating the practical application of the technology.
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