Literature DB >> 18678589

VistaClara: an expression browser plug-in for Cytoscape.

Robert Kincaid1, Allan Kuchinsky, Michael Creech.   

Abstract

SUMMARY: VistaClara is a plug-in for Cytoscape which provides a more flexible means to visualize gene and protein expression within a network context. An extended attribute browser is provided in the form of a graphical and interactive permutation matrix that resembles the heat map displays popular in gene-expression analysis. This extended browser permits a variety of display options and interactions not currently available in Cytoscape. AVAILABILITY: http://chianti.ucsd.edu/cyto_web/plugins/index.php.

Entities:  

Mesh:

Year:  2008        PMID: 18678589      PMCID: PMC2530886          DOI: 10.1093/bioinformatics/btn368

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


1 INTRODUCTION

Cytoscape (Shannon et al., 2003) is a freely available open source platform for the analysis of biological networks which is widely used by system biologists. Cytoscape provides facilities for incorporating node and edge attributes and mapping such data onto the network via visual encodings (color, shape, etc.). For protein- or gene-expression studies, the expression data for a given condition or treatment would correspond to a single attribute measured across a number of biomolecules. More specifically, this would typically correspond to a single micorarray experiment, or possibly a single mass spectrometry run. The default capabilities of Cytoscape are essentially limited to mapping only a single such experimental condition at a time (Cline et al., 2007). VistaClara was originally written as a stand-alone tool for interactively analyzing gene expression data from multiple experimental conditions. We soon realized VistaClara's usefulness as an expression browser for network analysis and prototyped a number of useful coordinated interactions between the tabular style of VistaClara and biological networks using our own proprietary network analysis tools. This investigation (Vailaya et al., 2005) led to a natural desire to extend Cytoscape with the same functionality. Hence, we have re-implemented and extended VistaClara as an attribute browser plug-in for Cytoscape (Fig. 1).
Fig. 1.

Cytoscape 2.6 showing the location and appearance of the VistaClara panel. Here, the table view shows a heat map display.

Cytoscape 2.6 showing the location and appearance of the VistaClara panel. Here, the table view shows a heat map display.

2 IMPLEMENTATION

The design of VistaClara is based on an approach informed by research in information visualization. In this article, we describe briefly the main features of the software. The reader can refer to the paper describing the original stand-alone version (Kincaid, 2004) for additional details.

2.1 Permutation matrix with overview

VistaClara starts with the traditional heat map visualization commonly used to display gene expression data, and extends this to a fully interactive permutation matrix supporting column and row rearrangement as described by Bertin (Bertin, 1981). Since sorting by a single row or column is often ineffective for analyzing expression data, VistaClara also allows sorting rows using measures of similarity between entire rows of expression data. A given row of interest is chosen, and the remaining rows are ordered by similarity (Euclidean or Pearson) to the chosen row. Similarity sorts can be performed almost as quickly as a standard sort, thereby retaining the benefits of a highly interactive row permutation operation while revealing more significant correlations. While heat map views are commonly used to view ratio-based expression data as a graphical matrix, there is good evidence that for small differences color intensity is difficult to visually resolve. Bertin and others have advocated size as a preferred, more visually comparable representation. We optionally replace the typical heat map rectangles with filled circles (called ‘ink blobs’), whose diameters are in proportion to the represented values. If the diameter goes beyond a critical threshold, the cell in which the circle appears is filled. This change in shape is an additional highly visible cue that the data has exceeded this threshold. VistaClara also provides an overview display of the entire data set in the form of a dynamic heat map (Fig. 2C). As rows and columns are rearranged, the overview is updated to reflect the change and any emerging correlations that might be visible beyond the tabular view. The overview can also be used to navigate to regions of interest by simply clicking on the appropriate location in the overview. A cursor (Fig. 2D) shows the user the portion of the full data set currently visible in the table view (Fig. 2B).
Fig. 2.

The main components of the VistaClara panel. (A) The main tool bar. (B) The graphical table view (in ink-blob mode). (C) Condensed heat map view of the entire data set. (D) A cursor showing the scroll position of the table view. Here, ink blobs become rectangular at 4-fold changes in gene expression.

The main components of the VistaClara panel. (A) The main tool bar. (B) The graphical table view (in ink-blob mode). (C) Condensed heat map view of the entire data set. (D) A cursor showing the scroll position of the table view. Here, ink blobs become rectangular at 4-fold changes in gene expression.

2.2 Coordintated network interactions

Integrating VistaClara directly into Cytoscape enables several useful coordinated interactions: Mapping of experimental conditions is easily managed by simply clicking on the appropriate table column header to select that column for network node coloring. For studying the dynamics of a system, the user can click the play button to automatically select each condition in succession for network node coloring. For time series experiments this permits the creation of an animated view of the network as it changes over time. Forward and reverse buttons allow user control for replaying specific conditions of interest. A mode is provided where selections are linked between the table and network views. This permits coordinated navigation. Selecting a single node in the network scrolls the table to reveal the corresponding row in the table. Selecting a cell in the table zooms into the neighborhood of the corresponding node in the network. Multiple selections are also supported in either view with full coordination between views.

2.3 Heat strips

VistaClara also provides a feature to view all expression data simultaneously as described previously in a study of coronary atherosclerosis (King et al., 2005). Each node is shown with an accompanying glyph in the form of a bar graph which depicts all expression values for that node. Redundant heat map coloring is used to reinforce both the heat map scheme as well as the interpretation of the bar graph. We call these glyphs heat strips, referring to their encoding relationship to heat maps. Figure 3 shows a display of cell cycle data (de Lichtenberg et al., 2005; Spellman et al., 1998). For these particular nodes, the sinusoidal behavior of the gene expression through two phases of cell cycle is quite obvious.
Fig. 3.

Heat strips display bar-graphs of all expression data for each node. Temporal patterns in time series data are readily apparent.

Heat strips display bar-graphs of all expression data for each node. Temporal patterns in time series data are readily apparent.

3 INSTALLATION

The current version of the VistaClara plug-in (Version 1.0) requires Cytoscape 2.6 and is freely available from the Cytoscape website or through the built-in Cytoscape plug-in manager. After installation, plug-in specific online help is accessible at run time and includes a short tutorial about data syncing as well as more detail about general usage. The help button is the yellow question mark seen in the toolbar (Fig. 2A). Conflict of Interest: none declared.
  6 in total

1.  Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Authors:  Paul Shannon; Andrew Markiel; Owen Ozier; Nitin S Baliga; Jonathan T Wang; Daniel Ramage; Nada Amin; Benno Schwikowski; Trey Ideker
Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

2.  An architecture for biological information extraction and representation.

Authors:  Aditya Vailaya; Peter Bluvas; Robert Kincaid; Allan Kuchinsky; Michael Creech; Annette Adler
Journal:  Bioinformatics       Date:  2004-12-17       Impact factor: 6.937

3.  Integration of biological networks and gene expression data using Cytoscape.

Authors:  Melissa S Cline; Michael Smoot; Ethan Cerami; Allan Kuchinsky; Nerius Landys; Chris Workman; Rowan Christmas; Iliana Avila-Campilo; Michael Creech; Benjamin Gross; Kristina Hanspers; Ruth Isserlin; Ryan Kelley; Sarah Killcoyne; Samad Lotia; Steven Maere; John Morris; Keiichiro Ono; Vuk Pavlovic; Alexander R Pico; Aditya Vailaya; Peng-Liang Wang; Annette Adler; Bruce R Conklin; Leroy Hood; Martin Kuiper; Chris Sander; Ilya Schmulevich; Benno Schwikowski; Guy J Warner; Trey Ideker; Gary D Bader
Journal:  Nat Protoc       Date:  2007       Impact factor: 13.491

4.  Pathway analysis of coronary atherosclerosis.

Authors:  Jennifer Y King; Rossella Ferrara; Raymond Tabibiazar; Joshua M Spin; Mary M Chen; Allan Kuchinsky; Aditya Vailaya; Robert Kincaid; Anya Tsalenko; David Xing-Fei Deng; Andrew Connolly; Peng Zhang; Eugene Yang; Clifton Watt; Zohar Yakhini; Amir Ben-Dor; Annette Adler; Laurakay Bruhn; Philip Tsao; Thomas Quertermous; Euan A Ashley
Journal:  Physiol Genomics       Date:  2005-06-07       Impact factor: 3.107

5.  Dynamic complex formation during the yeast cell cycle.

Authors:  Ulrik de Lichtenberg; Lars Juhl Jensen; Søren Brunak; Peer Bork
Journal:  Science       Date:  2005-02-04       Impact factor: 47.728

6.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization.

Authors:  P T Spellman; G Sherlock; M Q Zhang; V R Iyer; K Anders; M B Eisen; P O Brown; D Botstein; B Futcher
Journal:  Mol Biol Cell       Date:  1998-12       Impact factor: 4.138

  6 in total
  15 in total

Review 1.  Visualization of omics data for systems biology.

Authors:  Nils Gehlenborg; Seán I O'Donoghue; Nitin S Baliga; Alexander Goesmann; Matthew A Hibbs; Hiroaki Kitano; Oliver Kohlbacher; Heiko Neuweger; Reinhard Schneider; Dan Tenenbaum; Anne-Claude Gavin
Journal:  Nat Methods       Date:  2010-03       Impact factor: 28.547

Review 2.  Methods, Tools and Current Perspectives in Proteogenomics.

Authors:  Kelly V Ruggles; Karsten Krug; Xiaojing Wang; Karl R Clauser; Jing Wang; Samuel H Payne; David Fenyö; Bing Zhang; D R Mani
Journal:  Mol Cell Proteomics       Date:  2017-04-29       Impact factor: 5.911

3.  SpotXplore: a Cytoscape plugin for visual exploration of hotspot expression in gene regulatory networks.

Authors:  Michel A Westenberg; Jos B T M Roerdink; Oscar P Kuipers; Sacha A F T van Hijum
Journal:  Bioinformatics       Date:  2010-09-21       Impact factor: 6.937

4.  A travel guide to Cytoscape plugins.

Authors:  Rintaro Saito; Michael E Smoot; Keiichiro Ono; Johannes Ruscheinski; Peng-Liang Wang; Samad Lotia; Alexander R Pico; Gary D Bader; Trey Ideker
Journal:  Nat Methods       Date:  2012-11-06       Impact factor: 28.547

5.  Arena3D: visualizing time-driven phenotypic differences in biological systems.

Authors:  Maria Secrier; Georgios A Pavlopoulos; Jan Aerts; Reinhard Schneider
Journal:  BMC Bioinformatics       Date:  2012-03-22       Impact factor: 3.169

6.  Transcriptional responses to sucrose mimic the plant-associated life style of the plant growth promoting endophyte Enterobacter sp. 638.

Authors:  Safiyh Taghavi; Xiao Wu; Liming Ouyang; Yian Biao Zhang; Andrea Stadler; Sean McCorkle; Wei Zhu; Sergei Maslov; Daniel van der Lelie
Journal:  PLoS One       Date:  2015-01-21       Impact factor: 3.240

7.  NetworkPainter: dynamic intracellular pathway animation in Cytobank.

Authors:  Jonathan R Karr; Harendra Guturu; Edward Y Chen; Stuart L Blair; Jonathan M Irish; Nikesh Kotecha; Markus W Covert
Journal:  BMC Bioinformatics       Date:  2015-05-25       Impact factor: 3.169

8.  PhenoTimer: software for the visual mapping of time-resolved phenotypic landscapes.

Authors:  Maria Secrier; Reinhard Schneider
Journal:  PLoS One       Date:  2013-08-12       Impact factor: 3.240

9.  BirdsEyeView (BEV): graphical overviews of experimental data.

Authors:  Lifeng Zhang; Daniel Berleant; Yi Wang; Ling Li; Diane Cook; Eve Syrkin Wurtele
Journal:  BMC Bioinformatics       Date:  2012-09-11       Impact factor: 3.169

10.  3DScapeCS: application of three dimensional, parallel, dynamic network visualization in Cytoscape.

Authors:  Qi Wang; Biao Tang; Lifu Song; Biao Ren; Qun Liang; Feng Xie; Ying Zhuo; Xueting Liu; Lixin Zhang
Journal:  BMC Bioinformatics       Date:  2013-11-14       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.