The analysis of mixed short tandem repeat (STR) profiles has been long considered as a difficult challenge in the forensic DNA analysis. In the context of China, the current approach to analyze mixed STR profiles depends mostly on forensic manual method. However, besides the inefficiency, this technique is also susceptible to subjective biases in interpreting analysis results, which can hardly meet up with the growing demand for STR profiles analysis. In response, this study introduces an innovative method known as the global minimum residual method, which not only predicts the proportion of each contributor within a mixture, but also delivers accurate analysis results. The global minimum residual method first gives new definitions to the mixture proportion, then optimizes the allele model. After that, it comprehensively considers all loci present in the STR profile, accumulates and sums the residual values of each locus and selects the mixture proportion with the minimum accumulative sum as the inference result. Furthermore, the grey wolf optimizer is also employed to expedite the search for the optimal value. Notably, for two-person STR profiles, the high accuracy and remarkable efficiency of the global minimum residual method can bring convenience to realize extensive STR profile analysis. The optimization scheme established in this research has exhibited exceptional outcomes in practical applications, boasting significant utility and offering an innovative avenue in the realm of mixed STR profile analysis.
在法医DNA分析领域,混合短串联重复序列(short tandem repeats,STR)图谱的分析一直是研究难点。当前,国内主要依靠法医进行人工分析,不仅效率低下,分析结果还存在着主观性偏好,难以满足日益增长的STR图谱分析的需求。本文提出一种新的混合STR图谱分析方法——全局最小残差法,不仅可以计算出分析结果,还可以预测出每个组分的混合比例。该方法首先给混合比例赋予了新的定义,然后对等位基因模型进行优化,进而综合考虑STR图谱中的所有基因座,将每个基因座的残差值进行累加求和,选择累加和最小的混合比例作为推断结果,并使用灰狼优化算法快速寻找混合比例的最优值。对于二组分STR图谱,全局最小残差法能够兼顾分析的准确性和分析速度,有利于实现大量的图谱分析。本文提出的算法在实际应用中取得了不错的效果,具有较高的应用价值,可为混合STR图谱分析领域的研究提供新的解决方案。.
Keywords: allele model; forensic genetics; grey wolf optimizer; mixed STR profile.