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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: May 28, 2026

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

RNA-Seq analysis in MeV.

Eleanor A Howe1, Raktim Sinha, Daniel Schlauch

  • 1Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.

Bioinformatics (Oxford, England)
|October 7, 2011
PubMed
Summary
This summary is machine-generated.

This study enhances MultiExperiment Viewer (MeV) for analyzing large RNA sequencing (RNA-Seq) datasets. New tools enable biologists to easily process RNA-Seq data and perform differential expression analysis.

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Last Updated: May 28, 2026

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
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AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput sequencing generates large RNA-Seq datasets.
  • Biologist-friendly tools for RNA-Seq data analysis are limited.
  • MultiExperiment Viewer (MeV) is a popular Java-based application for gene expression analysis.

Purpose of the Study:

  • To enhance the MultiExperiment Viewer (MeV) for RNA-Seq data analysis.
  • To introduce RNA-Seq-specific functions into MeV.
  • To provide biologists with intuitive tools for complex RNA-Seq data interpretation.

Main Methods:

  • Integration of RNA-Seq analysis capabilities into the existing MeV platform.
  • Development of automatic conversion functions for raw RNA-Seq count data to RPKM/FPKM values.
  • Implementation of differential expression detection and functional annotation enrichment analysis modules.

Main Results:

  • MeV now supports the analysis of RNA-Seq data using its established graphical user interface.
  • New functionalities address the unique requirements of RNA-Seq data compared to traditional gene expression data.
  • Tools for data normalization, differential expression, and functional enrichment are now available within MeV.

Conclusions:

  • The enhanced MeV provides a powerful and accessible platform for RNA-Seq data analysis.
  • This upgrade empowers biologists to leverage advanced sequencing data with familiar tools.
  • The integration facilitates deeper insights into transcriptomic profiles and gene function.