StratomeX: Visual Analysis of Large‐Scale Heterogeneous Genomics Data for Cancer Subtype Characterization

Abstract

Identification and characterization of cancer subtypes are important areas of research that are based on the integrated analysis of multiple heterogeneous genomics datasets. Since there are no tools supporting this process, much of this work is done using ad-hoc scripts and static plots, which is inefficient and limits visual exploration of the data. To address this, we have developed StratomeX, an integrative visualization tool that allows investigators to explore the relationships of candidate subtypes across multiple genomic data types such as gene expression, DNA methylation, or copy number data. StratomeX represents datasets as columns and subtypes as bricks in these columns. Ribbons between the columns connect bricks to show subtype relationships across datasets. Drill-down features enable detailed exploration. StratomeX provides insights into the functional and clinical implications of candidate subtypes by employing small multiples, which allow investigators to assess the effect of subtypes on molecular pathways or outcomes such as patient survival. As the configuration of viewing parameters in such a multi-dataset, multi-view scenario is complex, we propose a meta visualization and configuration interface for dataset dependencies and data-view relationships. StratomeX is developed in close collaboration with domain experts. We describe case studies that illustrate how investigators used the tool to explore subtypes in large datasets and demonstrate how they efficiently replicated findings from the literature and gained new insights into the data.

On Computationally-Enhanced Visual Analysis of Heterogeneous Data and Its Application in Biomedical Informatics

“…Other examples include works accomplished within the Caleydo software for pathway analysis and associated experimental data by Lex et al [60][61][62]. In a recent work (see Figure 3), the integrated use of statistical computations is shown to be useful to characterize the groupings in the data [63].…”

Building applications for interactive data exploration in systems biology

“…The database service provides an open HTTP interface to biological databases for retrieving meta-data on genes and processes. We have currently packages for interfacing with E-utilities 12 , MSigDB 13 , Hugo Gene Nomenclature Committe (HGNC) 14 , and Kyoto Encyclopedia of Genes and Genomes (KEGG) 15 .…”

“…Users can add additional features, such as databases connections or new layouts, through Apps. One such app is cyREST which allows external network creation and analysis through a REST API [13] [14]; Pathfinder for exploring paths in large multivariate graphs [15]; UpSet to visualize and analyse sets, their intersections and aggregates [16]; Entourage and enRoute to explore and visualize biological pathways [17][18]; LineUp to explore rankings of items based on a set of attributes [19]; and Domino for exploring subsets across multiple tabular datasets [20].…”

MObjects--A Novel Method for the Visualization and Interactive Exploration of Defects in Industrial XCT Data

“…Instead of individual data points, they show data frequencies between the axes and visualize the relations between categories. StratomeX by Lex et al [16] was inspired by parallel sets, where datasets of genomic data are represented as columns and subtypes as bricks in the columns. Our MObject Set visualization in parallel alignment was inspired by these techniques (MObjects Exploration -Task 3).…”