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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
11.7K

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mirMachine: A One-Stop Shop for Plant miRNA Annotation
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A Verified Workflow for MiRNA-Seq Data Processing and Bioinformatics Analysis Using R.

Linxi Huang1, Dandan Chen1, Bo Yang2

  • 1Department of Nephrology, 905th Hospital of PLA Navy, Naval Medical University.

Journal of Visualized Experiments : Jove
|November 10, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a standardized R workflow for processing and analyzing microRNA sequencing (miRNA-Seq) data. The protocol ensures reproducible results for miRNA biomarker discovery and disease modeling.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • MicroRNAs (miRNAs) are key regulators of gene expression impacting health and disease.
  • High-throughput sequencing enables miRNA profiling, but requires standardized analysis.
  • Existing miRNA-Seq analysis pipelines lack comprehensive standardization.

Purpose of the Study:

  • To present a verified, reproducible R-based workflow for miRNA-Seq data analysis.
  • To facilitate robust interpretation of miRNA expression patterns.
  • To support miRNA biomarker discovery and disease mechanism studies.

Main Methods:

  • Development of an R workflow for end-to-end miRNA-Seq data processing.
  • Integration of established R packages for quality control, alignment, and quantification.
  • Inclusion of differential expression analysis, target prediction, and network construction modules.
  • Guidance on using curated databases and visualization tools like Cytoscape.

Main Results:

  • A flexible and transparent protocol for miRNA-Seq data analysis is established.
  • The workflow supports species-specific annotations and modular customization.
  • Enables robust statistical analysis and biological interpretation of miRNA functions.
  • Facilitates the study of miRNA-mRNA interactions and their role in diseases.

Conclusions:

  • The presented R workflow provides a standardized approach for miRNA-Seq data analysis.
  • It empowers researchers to gain meaningful biological insights from miRNA expression data.
  • This protocol is suitable for various applications, including biomarker discovery and multi-omics studies.