Ionascu Adrian, Ecovoiu Alexandru Al, Chifiriuc Mariana Carmen, Ratiu Attila Cristian
Drosophila Laboratory, Faculty of Biology, University of Bucharest, 060101 Bucharest, Romania.
Academy of Romanian Scientists, Ilfov 3, 050044 Bucharest, Romania.
Biotechniques. 2024 Dec;76(12):559-573. doi: 10.1080/07366205.2024.2442217. Epub 2024 Dec 24.
Gene expression assays that are based on quantitative real-time PCR (qRT-PCR) method are still very popular, therefore, we developed qDATA, an open-source R-based bioinformatics application that offers a quick and intuitive analysis of raw cycle threshold (Ct) values. The application relies on a straightforward data input consisting in Ct values and on other mandatory fields specifying the experimental and control groups. qDATA automatically performs descriptive statistics, normality and statistical testing on 2 (or ΔCt) and 2 terms calculated with Livak's method. We also propose a qRT-PCR data analysis framework that depends on performing exhaustive ΔCt calculations within discrete biological replicates (BRs) and subsequently using the Livak formula for the complete sets of available data. These prerequisites arguably lead to an improved data analysis and statistical relevance. The efficiency of our computing approach was tested using input Ct values corresponding to immune related gene expression evaluated in experimental infection of and workers. The presented results reveal that our working strategy is reliable and highlight the efficacy and performance of qDATA application.
基于定量实时PCR(qRT-PCR)方法的基因表达检测仍然非常流行,因此,我们开发了qDATA,这是一个基于R的开源生物信息学应用程序,可对原始循环阈值(Ct)值进行快速直观的分析。该应用程序依赖于由Ct值组成的直接数据输入以及指定实验组和对照组的其他必填字段。qDATA会自动对使用Livak方法计算的2(或ΔCt)和2项进行描述性统计、正态性和统计检验。我们还提出了一个qRT-PCR数据分析框架,该框架依赖于在离散生物重复(BR)内进行详尽的ΔCt计算,随后对整套可用数据使用Livak公式。这些前提条件可以说有助于改进数据分析和统计相关性。我们使用与在[具体实验对象]实验感染中评估的免疫相关基因表达相对应的输入Ct值测试了我们计算方法的效率。呈现的结果表明我们的工作策略是可靠的,并突出了qDATA应用程序的功效和性能。