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RNA-seq

RNA-seq

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...

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Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

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Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and

Matthew Beckers¹, Irina Mohorianu^1,2, Matthew Stocks¹

¹School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom.

RNA (New York, N.Y.)

|March 15, 2017

Summary

This study introduces a new pipeline for analyzing small RNA (sRNA) data, improving the understanding of gene expression regulation through RNA silencing. The UEA sRNA Workbench offers tools for comprehensive sRNA differential expression analysis.

Keywords:

UEA sRNA Workbench, quality checking differential expression high-throughput sequencing (HTS)microRNA (miRNA)normalization small RNA (sRNA)

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Last Updated: Mar 6, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

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Published on: November 7, 2025

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Published on: June 8, 2020

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

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Published on: March 7, 2018

Area of Science:

Molecular Biology
Bioinformatics
Genomics

Background:

High-throughput sequencing (HTS) reveals eukaryotic small RNA (sRNA) populations involved in gene regulation via RNA silencing.
Current tools inadequately mine complex sRNA data, hindering a full understanding of biological mechanisms.
Increased sequencing depth necessitates advanced analytical approaches for sRNA studies.

Purpose of the Study:

To present an interactive pipeline for comprehensive differential expression analysis of sRNA data sets.
To provide researchers with user-friendly tools for sRNA data preprocessing and analysis.
To facilitate a deeper understanding of sRNA roles in gene expression regulation.

Main Methods:

Development of a new interactive pipeline integrated into the UEA sRNA Workbench.
Inclusion of specialized tools for sRNA quality checking, normalization, and differential expression detection.
Application of the pipeline to *H. sapiens*, *B. terrestris*, and *A. thaliana* data sets.

Main Results:

The pipeline enables comprehensive analysis of sRNA differential expression and pattern identification.
Demonstrated utility on human, bumblebee, and thale cress data sets.
Comparison with existing methods highlights the pipeline's advantages in addressing sRNA analysis challenges.

Conclusions:

The UEA sRNA Workbench pipeline enhances the comprehensive study of differential gene expression in sRNA data.
The developed tools address limitations in current sRNA data mining, improving biological mechanism description.
This approach facilitates a more complete understanding of sRNA functions in eukaryotes.