Data for Paper: Advanced DNA fingerprints genotyping of chip electrophoresis samples

Large-scale comparative studies of DNA fingerprints prefer automated chip capillary electrophoresis instead of conventional gel planar electrophoresis due to the higher precision of the digitalization process. However, the determination of band sizes is still limited by the device resolution and sizing accuracy. Band matching, therefore, remains the key step in DNA fingerprint analysis. Current methods mostly evaluate only the pair similarity of the samples, using heuristically determined constant thresholds to evaluate the maximum allowed band size deviation. Such an approach significantly reduces the ability to distinguish between closely related samples. In this study, a new approach based on global multiple alignments of bands of all samples, with an adaptive threshold derived from the detailed migration analysis of a large number of real samples, is presented. The proposed approach allows accurate automated analysis of DNA fingerprint similarities for extensive epidemiological studies of bacterial strains, thereby helping to prevent the spread of dangerous microbial infections.

在DNA指纹（DNA fingerprint）的大规模比较研究中，由于数字化流程具备更高精度，自动化芯片毛细管电泳（automated chip capillary electrophoresis）相较于传统凝胶平板电泳（conventional gel planar electrophoresis）更受青睐。然而，条带尺寸的测定仍受限于设备分辨率与条带校准精度。因此，条带匹配仍是DNA指纹分析的核心步骤。现有方法大多仅评估样本间的成对相似性，通过启发式确定的恒定阈值来判定最大允许条带尺寸偏差。此类方法会显著削弱区分密切相关样本的能力。本研究提出了一种全新方法，该方法基于所有样本条带的全局多重比对，并通过对大量真实样本的详细迁移分析推导出自适应阈值。该方法可实现细菌菌株大规模流行病学研究中DNA指纹相似性的精准自动化分析，进而助力防范危险微生物感染的传播。