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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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Updated: Mar 26, 2026

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Cascade: an RNA-seq visualization tool for cancer genomics.

Aaron R Shifman¹, Radia M Johnson², Brian T Wilhelm³

¹Laboratory for high throughput genomics, Institute for Research in Immunology and Cancer, University of Montreal, Montreal, QC, Canada. ashif060@uottawa.ca.

|January 27, 2016

Summary

Cascade is a new web tool for 3D visualization of cancer genomics data. It integrates multiple data types like mutation and gene expression for intuitive exploration and hypothesis generation.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

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Published on: September 18, 2021

Area of Science:

Genomics
Bioinformatics
Cancer Research

Background:

Cancer genomics projects generate vast amounts of diverse patient sample data.
Current software limitations hinder integrated and intuitive visualization of this complex data.
Researchers often need multiple tools, preventing a unified view of their cohort data.

Purpose of the Study:

To present Cascade, a novel web-based tool for intuitive 3D visualization of cancer genomics data.
To address the need for integrated data exploration in cancer research.

Main Methods:

Developed a web-based tool named Cascade.
Implemented intuitive 3D visualization for RNA-seq data.
Integrated multiple data types (mutation, gene expression, alternative splicing frequency) display.
Enabled customization via user-defined parameters and biological pathways.
Utilized an underlying MySQL database for data access.

Main Results:

Cascade provides simultaneous display of multiple cancer genomics data types.
The tool offers a simplified, tuneable view of complex datasets.
User data can be overlaid onto predefined or custom biological pathways.
A space-saving menu allows for efficient data selection and parameter adjustment.

Conclusions:

There is a significant need for user-friendly software to explore large cancer genomics datasets.
Cascade offers a simple, intuitive, scalable, and customizable interface for data visualization.
The tool facilitates easier hypothesis generation for cancer researchers.