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.
Researchers from the University of Montreal have devloped 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.
Overview of Cascade organization
A cartoon view of Cascade is shown with the three principal components coloured. The relational database (blue) holds all user defined data (e.g. from RNA-seq experiments) along with pre-defined data for biological pathways, networks, disease associated genes, etc. A collection of Java/PHP scripts (pink) act as bridge between the database and the main webpage (grey) used for user interaction and data visualization
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.
Screenshot of data rendering on main webpage
Cascade uses a space-saving menu on the left-hand side of the screen to store functions to: (a) select features of the RNA-seq data to be displayed, (b) select biological pathways to overlay data onto, (c) select datasets to use for visualization of features selected (using a) and (d) restrict the colouring thresholds for features based on custom or predefined disease gene lists. The “modify ranges” button (top centre) allows users to alter the cohort frequency thresholds (a) required for node colour changes (mutations) or ring appearance (splicing). Additional buttons (top) toggle display of guide rings, generate (.jpg) screen images or open tool documentation