Zhuang Wei, Liu Jessica
Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas, United States of America.
Department of Statistics, Rice University, Houston, Texas, United States of America.
PLoS One. 2025 Sep 2;20(9):e0330729. doi: 10.1371/journal.pone.0330729. eCollection 2025.
As a common experimental technique, qPCR (Quantitative Real-time Polymerase Chain Reaction) is widely used to measure levels of nucleic acids, e.g., microRNAs and messenger RNA. While providing accurate and complete data, researchers have inevitably encountered uncertainly determined qPCR data because of intrinsically low amounts of biological material. The presence of incomplete or uncertain qPCR data challenges interpretation accuracy. This study presents a web application that integrates two sophisticated statistical methods - a flexible regression approach and a two-group hypothesis testing technique - to enhance the accuracy and robustness of qPCR data analysis with informative but uncertainly determined observations. To demonstrate the versatility and efficacy of our MCTOT (Multi-Functional Cycle-To-Threshold Statistical Analysis Tool) application, this study presents two distinct examples employing two-group hypothesis testing. The first example delves into an analysis of pathogens in wastewater, an area gaining increasing relevance for public health surveillance. The second example illustrates an application in the realm of liquid biopsy, a rapidly evolving field in disease diagnostics, monitoring, and early treatment. Moreover, the application's process is further exhibited through another liquid biopsy example, wherein the flexible regression method is employed to detect the hemolysis effect on a molecular target. These examples demonstrate the tool's capacity to not only identify significant differences between groups but also to quantify the effect size, a crucial aspect in biomedical research. The MCTOT web application stands as a pioneering step toward empowering researchers to harness the full potential of qPCR data, especially when dealing with informative but uncertainly determined observations. It also paves the way for further development of web-based tools that adhere to the refined CTOT (Cycle-To-Threshold) methodology, opening new avenues in qPCR data analysis and interpretation. The developed application can be accessed online through Shinyapps.io at https://ctot.shinyapps.io/bioinformatics/ for open access.
作为一种常见的实验技术，qPCR（定量实时聚合酶链反应）被广泛用于测量核酸水平，例如微小RNA和信使RNA。虽然能提供准确和完整的数据，但由于生物材料的内在含量低，研究人员不可避免地遇到了qPCR数据测定不确定的情况。不完整或不确定的qPCR数据的存在对解释准确性提出了挑战。本研究提出了一个网络应用程序，它集成了两种复杂的统计方法——一种灵活的回归方法和一种两组假设检验技术——以提高qPCR数据分析的准确性和稳健性，这些分析基于信息丰富但测定不确定的观察结果。为了证明我们的MCTOT（多功能循环阈值统计分析工具）应用程序的多功能性和有效性，本研究给出了两个采用两组假设检验的不同示例。第一个示例深入分析了废水中的病原体，这一领域对公共卫生监测的相关性日益增加。第二个示例说明了在液体活检领域的应用，液体活检是疾病诊断、监测和早期治疗中一个快速发展的领域。此外，通过另一个液体活检示例进一步展示了该应用程序的过程，其中采用灵活回归方法来检测溶血对分子靶点的影响。这些示例证明了该工具不仅能够识别组间的显著差异，还能量化效应大小，这是生物医学研究中的一个关键方面。MCTOT网络应用程序是朝着使研究人员能够充分利用qPCR数据的全部潜力迈出的开创性一步，特别是在处理信息丰富但测定不确定的观察结果时。它还为遵循改进的CTOT（循环阈值）方法的基于网络的工具的进一步开发铺平了道路，为qPCR数据分析和解释开辟了新途径。所开发的应用程序可通过Shinyapps.io在线访问，网址为https://ctot.shinyapps.io/bioinformatics/ ，以供开放获取。
