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. 2015 Jul 1;43(W1):W560-5.
doi: 10.1093/nar/gkv450. Epub 2015 May 9.

NaviCell Web Service for Network-Based Data Visualization

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Free PMC article

NaviCell Web Service for Network-Based Data Visualization

Eric Bonnet et al. Nucleic Acids Res. .
Free PMC article

Abstract

Data visualization is an essential element of biological research, required for obtaining insights and formulating new hypotheses on mechanisms of health and disease. NaviCell Web Service is a tool for network-based visualization of 'omics' data which implements several data visual representation methods and utilities for combining them together. NaviCell Web Service uses Google Maps and semantic zooming to browse large biological network maps, represented in various formats, together with different types of the molecular data mapped on top of them. For achieving this, the tool provides standard heatmaps, barplots and glyphs as well as the novel map staining technique for grasping large-scale trends in numerical values (such as whole transcriptome) projected onto a pathway map. The web service provides a server mode, which allows automating visualization tasks and retrieving data from maps via RESTful (standard HTTP) calls. Bindings to different programming languages are provided (Python and R). We illustrate the purpose of the tool with several case studies using pathway maps created by different research groups, in which data visualization provides new insights into molecular mechanisms involved in systemic diseases such as cancer and neurodegenerative diseases.

Figures

Figure 1.
Figure 1.
General architecture of the NaviCell Web service server. Client software (light blue layer) communicates with the server (red layer) through standard HTTP requests using the standard JSON format to encode data (RESTful web service, dark blue layer). A session (with a unique ID) is established between the server and the browser (yellow layer) through Ajax communication channel to visualize the results of the commands send by the software client. It is worth noticing that communication channels are bidirectional, i.e. the client software can send data (e.g. an expression data matrix) to the server, but it can also receive data from the server (e.g. a list of HUGO gene symbols contained in a map).
Figure 2.
Figure 2.
Visualization of multiple data types for two different prostate cancer cell lines. Transcriptomic, gene copy-number values and gene mutations (24) are mapped on the Cell Cycle map. (A) Hormone-sensitive prostate cancer cell line (LNCaP). (B) Hormone-refractory prostate cancer cell line (DU145). Expression data is visualized using the map staining technique, i.e. colored territories around entities, ranging from low (green) to high expression values (red). Copy-number values are represented by glyphs (squares) with blue color indicating gene loss (values of −1 and lower) and yellow color indicating amplification (values of 1 and higher). Mutated genes are depicted by cyan triangles.
Figure 3.
Figure 3.
Visualization of two different data types on the Alzheimer's disease (AD) pathway map. (A) Top-level view expression data are visualized with map staining (see Figure 2 legend). Frequently mutated genes are indicated by glyphs (blue triangles), with the size of the glyph proportional to the mutation frequency. (B–D) represent zooms on known key regulators of (B) apoptosis, (C) blood brain barrier and (D) MAPK signaling pathway. Background colors represent expression values as in (A), while barplots illustrate tissue-specific expression values for frontal cortex (FC), thalamo-cortical area (TC) and hippocampus (HI).

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