Chilimoniuk Jarosław, Erol Anna, Rödiger Stefan, Burdukiewicz Michał
Clinical Research Centre, Medical University of Białystok, Białystok, Poland.
Institute of Biotechnology, Faculty Environment and Natural Sciences, Brandenburg University of Technology Cottbus - Senftenberg, Senftenberg, Germany.
Comput Struct Biotechnol J. 2024 Apr 30;23:1951-1958. doi: 10.1016/j.csbj.2024.04.061. eCollection 2024 Dec.
NanoString nCounter is a medium-throughput technology used in mRNA and miRNA differential expression studies. It offers several advantages, including the absence of an amplification step and the ability to analyze low-grade samples. Despite its considerable strengths, the popularity of the nCounter platform in experimental research stabilized in 2022 and 2023, and this trend may continue in the upcoming years. Such stagnation could potentially be attributed to the absence of a standardized analytical pipeline or the indication of optimal processing methods for nCounter data analysis. To standardize the description of the nCounter data analysis workflow, we divided it into five distinct steps: data pre-processing, quality control, background correction, normalization and differential expression analysis. Next, we evaluated eleven R packages dedicated to nCounter data processing to point out functionalities belonging to these steps and provide comments on their applications in studies of mRNA and miRNA samples.
NanoString nCounter是一种用于mRNA和miRNA差异表达研究的中通量技术。它具有多个优点,包括无需扩增步骤以及能够分析低级别样本。尽管具有相当大的优势,但nCounter平台在实验研究中的受欢迎程度在2022年和2023年趋于稳定,并且这种趋势在未来几年可能会持续。这种停滞可能归因于缺乏标准化的分析流程或nCounter数据分析的最佳处理方法的指示。为了标准化nCounter数据分析工作流程的描述,我们将其分为五个不同的步骤:数据预处理、质量控制、背景校正、归一化和差异表达分析。接下来,我们评估了十一个专门用于nCounter数据处理的R包,以指出属于这些步骤的功能,并对它们在mRNA和miRNA样本研究中的应用提供评论。