Challenges and opportunities in processing NanoString nCounter data

Jarosław Chilimoniuk; Anna Erol; Stefan Rödiger; Michał Burdukiewicz

doi:10.1016/j.csbj.2024.04.061

Challenges and opportunities in processing NanoString nCounter data

Comput Struct Biotechnol J. 2024 Apr 30:23:1951-1958. doi: 10.1016/j.csbj.2024.04.061. eCollection 2024 Dec.

Authors

Jarosław Chilimoniuk¹, Anna Erol¹, Stefan Rödiger², Michał Burdukiewicz^{3

1}

Affiliations

¹ Clinical Research Centre, Medical University of Białystok, Białystok, Poland.
² Institute of Biotechnology, Faculty Environment and Natural Sciences, Brandenburg University of Technology Cottbus - Senftenberg, Senftenberg, Germany.
³ Institute of Biotechnology and Biomedicine, Autonomous University of Barcelona, Barcelona, Spain.

Abstract

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.

Keywords: Background correction; Differential expression; NanoString; Normalization; mRNA; miRNA; nCounter; nSolver.

Publication types

Review