In the present study, we developed a novel digital coding combination analysis (DCCA) to analyze the gene mutation based on the sample combination principle. The principle is that any numerically named sample is divided into two groups, any two samples are not grouped in the same two groups, and any sample can be tested within the detection limit. Therefore, we proposed a specific combination that N samples were divided into M groups. Then N samples were analyzed, which could obtain the mutation results of M mixed groups. If only two groups showed positive (mutant type) signals, the same sample number from two positive signal groups would be the positive sample, and the remaining samples were negative (wild type). If three groups or more exhibited positive results, the same sample number from three positive signal groups would be the positive sample. If some samples remained uncertain, individual samples could be analyzed on a small scale. In the present study, we used the two genotypes of a mutation site (A5301G) to verify whether it was a useful and promising method. The results showed that we could quantitatively detect mutations and demonstrate 100% consistent results against a panel of defined mixtures with the detection limit using pyrosequencing. This method was suitable, sensitive, and reproducible for screening and analyzing low-frequency mutation samples, which could reduce reagent consumption and cost by approximately 70–80% compared with conventional clinical methods.

中文翻译：

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使用焦磷酸测序进行突变基因分型的数字编码组合分析

在本研究中，我们开发了一种基于样本组合原理的新型数字编码组合分析（DCCA）来分析基因突变。其原理是任何有数字命名的样品分为两组，任何两个样品不属于同一组，任何样品都可以在检出限内进行检测。因此，我们提出了一个特定的组合，将N个样本分为M个组。然后对N个样本进行分析，可以得到M的突变结果混合组。如果只有两组显示阳性（突变型）信号，则两个阳性信号组中相同的样本数为阳性样本，其余样本为阴性（野生型）。如果三组或更多组显示阳性结果，则三个阳性信号组中相同的样本数将是阳性样本。如果某些样本仍然不确定，则可以对单个样本进行小规模分析。在本研究中，我们使用突变位点 (A5301G) 的两种基因型来验证它是否是一种有用且有前途的方法。结果表明，我们可以定量检测突变，并针对一组具有检测限的定义混合物使用焦磷酸测序证明 100% 一致的结果。该方法适用、灵敏、