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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.
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Genomics

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Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
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Related Experiment Video

Updated: Feb 21, 2026

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

Viewing RNA-seq data on the entire human genome.

Eric M Weitz¹, Lorena Pantano², Jingzhi Zhu³

¹National Center for Biotechnology Information, U.S. National Library of Medicine, Bethesda, MD, 20894, USA.

|October 6, 2017

Summary

RNA-Seq Viewer is a new web tool for visualizing genome-wide expression data from NCBI databases. This application prototype allows researchers to easily explore RNA sequencing data from SRA and GEO.

Keywords:

RNA-seq ideogram javascript next generation sequencing

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Area of Science:

Bioinformatics
Genomics
Computational Biology

Background:

Accessing and visualizing large-scale RNA sequencing data from public repositories like NCBI's Sequence Read Archive (SRA) and Gene Expression Omnibus (GEO) can be challenging for researchers.
There is a need for user-friendly tools to facilitate the exploration of genome-wide expression patterns.

Purpose of the Study:

To develop and present RNA-Seq Viewer, a novel web application for visualizing genome-wide expression data.
To enable researchers to easily access and interpret expression data from SRA and GEO.

Main Methods:

A web application prototype was developed during a three-day hackathon.
The backend data pipeline was built and deployed on Amazon Web Services (AWS) EC2 instances.
Source code was made publicly available on GitHub.

Main Results:

RNA-Seq Viewer provides a platform for visualizing genome-wide expression data.
The application integrates data from NCBI's SRA and GEO databases.
A functional prototype was successfully developed and deployed.

Conclusions:

RNA-Seq Viewer offers a valuable resource for researchers studying gene expression.
The tool simplifies the process of exploring large-scale transcriptomic datasets.
The open-source nature of the code encourages community development and adoption.