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Related Concept Videos

RNA-seq03:21

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 microarray-based...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

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Related Experiment Video

Updated: Jun 5, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
05:07

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

Published on: November 7, 2025

A pipeline for RNA-seq data processing and quality assessment.

Angela Goncalves1, Andrew Tikhonov, Alvis Brazma

  • 1EMBL Outstation-Hinxton, European Bioinformatics Institute, Cambridge, UK. angela.goncalves@ebi.ac.uk

Bioinformatics (Oxford, England)
|January 15, 2011
PubMed
Summary
This summary is machine-generated.

We developed ArrayExpressHTS, an R pipeline for processing RNA-seq data, enabling gene expression analysis and quality assessment from raw sequence files. This tool supports local or cloud-based execution for diverse RNA-seq datasets.

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Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
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Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

Related Experiment Videos

Last Updated: Jun 5, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
05:07

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

Published on: November 7, 2025

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
07:30

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput sequencing transcriptional profiling (RNA-seq) generates large, complex datasets.
  • Standardized pre-processing and analysis pipelines are crucial for reliable RNA-seq data interpretation.
  • Existing tools may lack comprehensive features for quality assessment and downstream integration.

Purpose of the Study:

  • To introduce ArrayExpressHTS, an R-based pipeline for RNA-seq data analysis.
  • To provide a tool for pre-processing, expression estimation, and quality assessment of RNA-seq datasets.
  • To facilitate the analysis of both user-generated and public RNA-seq data.

Main Methods:

  • Development of an R-based pipeline named ArrayExpressHTS.
  • Integration of functionalities for raw sequence file processing.
  • Implementation of gene or transcript expression estimation.
  • Inclusion of data quality assessment modules with web report generation.
  • Support for local and distributed R-cloud farm execution.

Main Results:

  • ArrayExpressHTS processes raw RNA-seq data into standard Bioconductor R objects.
  • The pipeline generates gene or transcript measurements suitable for downstream analyses.
  • Comprehensive web reports are produced for data quality assessment.
  • The tool is adaptable for both personal datasets and public archives like ArrayExpress.

Conclusions:

  • ArrayExpressHTS offers a robust and flexible solution for RNA-seq data analysis.
  • The pipeline enhances the accessibility and reliability of RNA-seq data interpretation.
  • It supports efficient analysis across various computational environments, from local machines to cloud platforms.