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The NanoString nCounter platform, used for mRNA and miRNA studies, faces stagnant popularity due to a lack of standardized analysis. This study evaluates R packages to establish optimal data processing workflows for nCounter data.

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Area of Science:

  • Molecular biology
  • Bioinformatics
  • Genomics

Background:

  • The NanoString nCounter is a medium-throughput platform for mRNA and miRNA differential expression analysis.
  • It offers advantages like no amplification step and analysis of low-grade samples.
  • Platform popularity has stabilized, potentially due to a lack of standardized analytical pipelines.

Purpose of the Study:

  • To standardize the description of the nCounter data analysis workflow.
  • To evaluate R packages for nCounter data processing.
  • To provide guidance on optimal methods for mRNA and miRNA sample analysis.

Main Methods:

  • Divided nCounter data analysis into five steps: pre-processing, quality control, background correction, normalization, and differential expression analysis.
  • Evaluated eleven R packages for their functionalities within these steps.
  • Assessed package applications for mRNA and miRNA studies.

Main Results:

  • Identified functionalities of eleven R packages for nCounter data analysis.
  • Provided comments on the application of these R packages for mRNA and miRNA samples.
  • Highlighted the need for standardized workflows.

Conclusions:

  • Standardized data analysis workflows are crucial for the NanoString nCounter platform.
  • Evaluation of R packages offers guidance for optimal nCounter data processing.
  • This work aims to support researchers in maximizing the utility of nCounter technology.