Gene library acquisition method for improving single cell amplification genomic coverage

CN121999874BActive Publication Date: 2026-06-09MOBIDROP (ZHEJIANG) CO LTD +1

Patent Information

Authority / Receiving Office: CN · China
Patent Type: Patents(China)
Current Assignee / Owner: MOBIDROP (ZHEJIANG) CO LTD
Filing Date: 2026-04-08
Publication Date: 2026-06-09

AI Technical Summary

Technical Problem

In existing single-cell sequencing technologies, the coverage of single-cell amplified genome is insufficient, affecting the depth and reliability of subsequent analysis. Moreover, existing methods are either costly or have limited effectiveness.

Method used

By constructing a composite library system consisting of long-fragment original libraries and short-fragment sub-libraries, and combining a prefix tree data structure and a dynamic threshold algorithm, intelligent merging of cross-library data is achieved, effectively identifying valid single-cell data and removing noise to generate high-quality gene library data.

Benefits of technology

This significantly improved the coverage and data quality of single-cell amplified genomes, ensuring the accuracy and reliability of the merging operation and enhancing the precision of subsequent analyses.

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Abstract

The present application relates to the field of biological information, and discloses a gene library acquisition method for improving single cell amplification genome coverage. In view of the problem of insufficient single cell amplification genome coverage, the gene library acquisition method provides a strategy of composite library construction and optimized data integration, comprising: for the same single cell sample, constructing at least one original library and one sub-library with different average fragment lengths, and performing sequencing; through a self-definable sequence feature detection method, the sequencing data is subjected to Barcode splitting and effective single cell identification; then, according to the identification result of the effective single cell, all sequencing sequence data of the same single cell is identified, collected and merged to generate the corresponding integrated sequence data set of the single cell, and the gene library data of the single cell is obtained. The SAG coverage of the obtained gene library data is high, and the gene library data has high reliability and application value for the downstream genome analysis of the single cell.

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