Zalewski Daniel, Bogucka-Kocka Anna
Chair and Department of Biology and Genetics, Medical University of Lublin, 4a Chodźki St, 20-093, Lublin, Poland.
Sci Rep. 2025 Aug 13;15(1):29762. doi: 10.1038/s41598-025-11822-0.
Relative quantification of gene expression is a fundamental method used in the molecular biology field to analyse real-time PCR data to determine transcriptional differences between groups of samples (or technical replicates of a single sample). The main methods used for relative quantification of gene expression are delta Ct methods that allow to compare means of gene expression between groups of samples without preparing a standard curve. Despite the availability of several tools for delta Ct methods, it is difficult to select the best one that would be characterized by sufficient flexibility and comprehensive functionality. Therefore, we developed the RQdeltaCT R package, which was designed to analyse real-time PCR data for the relative quantification of gene expression using delta Ct methods (including 2 and 2 methods), either to compare independent groups of samples or groups with paired samples. Furthermore, the package offers functions that cover other essential steps of analysis, including importing datasets, multistep quality control of data, numerous visualisations, and enrichment of the standard workflow with additional analyses (correlation analysis, Receiver Operating Characteristic analysis, linear and logistic regression). All obtained results can be conveniently saved as tables and publication-ready images. The RQdeltaCT package has been designed with the intention of being friendly to beginners in R programming. The package (version 1.3.2) is freely available on the GitHub ( https://github.com/Donadelnal/RQdeltaCT ) and CRAN ( https://CRAN.R-project.org/package=RQdeltaCT ) repositories.
基因表达的相对定量是分子生物学领域用于分析实时PCR数据以确定样本组(或单个样本的技术重复)之间转录差异的基本方法。用于基因表达相对定量的主要方法是ΔCt方法,该方法无需制备标准曲线即可比较样本组之间的基因表达均值。尽管有多种用于ΔCt方法的工具,但很难选择出具有足够灵活性和全面功能的最佳工具。因此,我们开发了RQdeltaCT R包,其旨在使用ΔCt方法(包括2 - ΔΔCt和2-ΔΔCt方法)分析实时PCR数据以进行基因表达的相对定量,既可以比较独立的样本组,也可以比较配对样本组。此外,该包还提供了涵盖其他重要分析步骤的功能,包括导入数据集、数据的多步质量控制、大量可视化以及通过额外分析(相关性分析、受试者工作特征分析、线性和逻辑回归)丰富标准工作流程。所有获得的结果都可以方便地保存为表格和可用于发表的图像。RQdeltaCT包的设计初衷是对R编程初学者友好。该包(版本1.3.2)可在GitHub(https://github.com/Donadelnal/RQdeltaCT)和CRAN(https://CRAN.R - project.org/package = RQdeltaCT)存储库中免费获取。