Visual Exploration of Three-Dimensional Gene Expression Using Physical Views and Linked Abstract Views

Abstract

During animal development, complex patterns of gene expression provide positional information within the embryo. To better understand the underlying gene regulatory networks, the Berkeley Drosophila Transcription Network Project (BDTNP) has developed methods that support quantitative computational analysis of three-dimensional (3D) gene expression in early Drosophila embryos at cellular resolution. We introduce PointCloudXplore, an interactive visualization tool that supports visual exploration of relationships between different genes’ expression using a combination of established visualization techniques. Two aspects of gene expression are of particular interest: (i) gene expression patterns defined by the spatial locations of cells expressing a gene, and (ii) relationships between the expression levels of multiple genes. PointCloudXplore provides users with two corresponding classes of data views: (i) Physical Views based on the spatial relationships of cells in the embryo, and (ii) Abstract Views that discard spatial information and plot expression levels of multiple genes with respect to each other. Cell Selectors highlight data associated with subsets of embryo cells within a View. Using linking, these selected cells can be viewed in multiple representations. We describe PCX as a 3D gene expression visualization tool and provide examples of how it has been used by BDTNP biologists to generate new hypotheses.

Assembling models of embryo development: Image analysis and the construction of digital atlases

“…Some relevant instances include: FlyEx (Pisarev et al, 2009), GoFigure (Gouaillard et al, 2007), PointCloudExplore (Weber et al, 2009;Rubel et al, 2010), Mov-IT (Olivier et al, 2010), BrainExplorer (Lau et al, 2008), BrainGazer (Bruckner et al, 2009), CellProfiler (Jones et al, 2008), and V3D (Peng etal., 2010).…”

Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-Energy Physics

“…To allow relationships between multiple transcription factors and their target genes to be compared in a common coordinate framework, Single PointClouds are registered to create Virtual PointClouds (also called Expression Atlases) describing the average expression of many genes in a single virtual embryo model [161] (see Section 3.1.4.3). The embryo registration process is described in detail in [161] The visualization system PointCloudXplore (PCX) is used for visual analysis of Single as well as Virtual PointClouds [157,159] …”

“…PointCloudXplore (PCX) 2 is a visualization system specifically developed for the analysis of 3D gene expression data [157,159] [137]. PCX is the standard visual analysis software of the BDTNP and integrates physical and abstract data views in a common framework using the established concept of brushing and linking (see Section 2.3).…”

“…In more complex cases, such as scattered data, a topology may not be given and must be defined first. In the case of 3D gene expression data, the neighborhood of a cell is defined based on the approximated Voronoi diagram of the embryo's blastoderm surface [159] (see Figure 2.11c).…”

“…Region-growing is used in the context of 3D gene expression data for automatic seed cell selection [159] (see Section 4.2.2.2). This research also employs region-growing methods based on three-dimensional histograms of the data for identification of particle bunches in laser wakefield particle accelerator simulation data (see Section 5.6.4).…”