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BMC Genomics. 2016 Jan 25;17:75. doi: 10.1186/s12864-016-2389-8.

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

Author information

1
Laboratory for high throughput genomics, Institute for Research in Immunology and Cancer, University of Montreal, Montreal, QC, Canada. ashif060@uottawa.ca.
2
Laboratory for high throughput genomics, Institute for Research in Immunology and Cancer, University of Montreal, Montreal, QC, Canada. radia.johnson@alum.utoronto.ca.
3
Laboratory for high throughput genomics, Institute for Research in Immunology and Cancer, University of Montreal, Montreal, QC, Canada. brian.wilhelm@umontreal.ca.

Abstract

BACKGROUND:

Cancer genomics projects are producing ever-increasing amounts of rich and diverse data from patient samples. The ability to easily visualize this data in an integrated an intuitive way is currently limited by the current software available. As a result, users typically must use several different tools to view the different data types for their cohort, making it difficult to have a simple unified view of their data.

RESULTS:

Here we present Cascade, a novel web based tool for the intuitive 3D visualization of RNA-seq data from cancer genomics experiments. The Cascade viewer allows multiple data types (e.g. mutation, gene expression, alternative splicing frequency) to be simultaneously displayed, allowing a simplified view of the data in a way that is tuneable based on user specified parameters. The main webpage of Cascade provides a primary view of user data which is overlaid onto known biological pathways that are either predefined or added by users. A space-saving menu for data selection and parameter adjustment allows users to access an underlying MySQL database and customize the features presented in the main view.

CONCLUSIONS:

There is currently a pressing need for new software tools to allow researchers to easily explore large cancer genomics datasets and generate hypotheses. Cascade represents a simple yet intuitive interface for data visualization that is both scalable and customizable.

PMID:
26810393
PMCID:
PMC4727405
DOI:
10.1186/s12864-016-2389-8
[Indexed for MEDLINE]
Free PMC Article

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