NaviCell Web Service for network-based data visualization
NaviCell Web Service for network-based data visualization
Eric Bonnet 0 1 2
Eric Viara 3
Inna Kuperstein 0 1 2
Laurence Calzone 0 1 2
David P. A.
Cohen 0 1 2
Emmanuel Barillot 0 1 2
Andrei Zinovyev 0 1 2
0 Mines ParisTech , 77300 Fontainebleau , France
1 INSERM, U900 , 75248 Paris , France
2 Institut Curie , 26 rue d'Ulm, 75248 Paris , France
3 Sysra , 91330 Yerres , France
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 largescale 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.
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INTRODUCTION
Biology is a scientific discipline deeply grounded in
visual representations serving for communicating results and
ideas. Nowadays, there is a strong incentive to provide
interactive web-based visual representations, that users can
easily adapt to address a biological question. Modern
molecular biology is particularly demanding for new tools that
can represent numerous ‘omics’ data in a meaningful way.
Visualizing quantitative ‘omics’ data in the context of
biological networks provides insights into the molecular
mechanisms in healthy tissues and in diseases (1,2). This is one of
the most demanded features of existing pathway databases
such as KEGG, Reactome and BioCyc (3–5). To answer
this need, many tools have been developed allowing
mapping ‘omics’ data on top of biological networks (6–9). These
tools use the content of existing pathway databases to
retrieve the pathway information through dedicated
application programming interface (API). In addition, some
pathway databases provide graphical user interfaces (GUI) to
perform data visualization, on interactive pathway maps.
When a user faces the necessity to visualize the ‘omics’
data on biological networks, there are currently only two
options available. The first is to use a graphical interface of
a suitable pathway database, which can be a tedious manual
work. The second is to use one of the available standalone or
web-based tools for creating static images of colored
pathways which are not interactive anymore, and do not allow
browsing the molecular interactions. Currently, there is a
lack of well-developed APIs that allow applying data
visualization programmatically on top of biological networks,
such that the ‘omics’ data can be browsed simultaneously
with the pathway information.
Available network-based methods for data visualization
have several common limitations. First, most of them do not
provide any possibility of data abstraction and do not
provide a possibility of visualizing coarse-grained trends in the
‘omics’ data. This is needed if, for example, there is a wish
to visualize the whole transcriptome of a cell or a group of
samples on a large network, representing an important part
of the cellular interactome. Current methods usually attach
some elements of the standard scientific graphics
(gradient color, heatmaps, barplots) to the individual elements of
pathway maps, which makes the visualization hardly
readable at higher levels of zooming as well as the map content
itself. Second, most of data visualization tools are specific to
a particular pathway database structure, format and
graphical pathway representation. This limits the use of data
visualization on user-defined maps. Third, APIs for
programmatic web-based data visualization are rudimentary or do
not exist.
To overcome some of these limitations, we have
developed NaviCell Web Service tool. It allows visualizing
‘omics’ data via GUI and flexible API using standard and
advanced methods of data visualization, including a
possibility to perceive the mapping of data at different network
scales. The NaviCell Web Service can exploit pathway maps
created by users or from existing databases, including large
network maps with thousands of elements.
The NaviCell Web Service for Network-based Data
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