Visualize the relationships between miRNAs and genes in a biological pathway

This function can be used to plot augmented pathways created by the topologicalAnalysis() function. In particular, given a valid object of class IntegrativePathwayAnalysis, this function allows to produce a network graph for a specified biological pathway, alongside with expression fold changes. In this way, augmented pathways made of both miRNAs and genes can be visually explored to better investigate the consequences of miRNA/gene dysregulations.

Usage

visualizeNetwork(
  object,
  pathway,
  algorithm = "dot",
  fontsize = 14,
  lfcScale = c("royalblue", "white", "red"),
  nodeBorderCol = "black",
  nodeTextCol = "black",
  edgeCol = "darkgrey",
  edgeWidth = 1,
  subgraph = NULL,
  highlightNodes = NULL,
  highlightCol = "gold",
  highlightWidth = 2,
  legendColorbar = TRUE,
  legendInteraction = TRUE,
  title = NULL,
  titleCex = 2,
  titleFace = 1
)

Arguments

object: An object of class IntegrativePathwayAnalysis containing the results of a miRNA-mRNA pathway analysis
pathway: The name of the biological pathway to show. The available pathways for a given database can be seen through the listPathways() function
algorithm: The layout algorithm used to arrange nodes in the network. It must be one of dot (default), circo, fdp, neato, osage or twopi. For more information regarding these algorithms, please check the details section
fontsize: The font size of each node in the graph. Default is 14
lfcScale: It must be a character vector of length 3 containing valid R color names for creating a gradient of log2 fold changes. The first value refers to downregulation, the middle one to stable expression, and the last one to upregulation. Default value is c('royalblue', 'white', 'red'). Available color formats include color names, such as 'blue' and 'red', and hexadecimal colors specified as #RRGGBB
nodeBorderCol: It must be an R color name that specifies the color of node borders. Default is black. Available color formats include color names, such as 'blue' and 'red', and hexadecimal colors specified as #RRGGBB
nodeTextCol: It must be an R color name that specifies the color of miRNA/gene names. Default is black. Available color formats include color names, such as 'blue' and 'red', and hexadecimal colors specified as #RRGGBB
edgeCol: It must be an R color name that specifies the color of edges between nodes. Default is darkgrey. Available color formats include color names, such as 'blue' and 'red', and hexadecimal colors specified as #RRGGBB
edgeWidth: The width of edges. Default is 1
subgraph: An optional character vector containing the nodes that you want to maintain in the final plot. All the other nodes will not be shown. This is useful to display specific features of extremely messy graphs. Default is NULL
highlightNodes: A character vector containing the names of nodes that you want to highlight. Default is NULL not to highlight any nodes. See the details section for additional information
highlightCol: It must be an R color name that specifies the color of edges and borders for highlighted nodes. Default is gold. Available color formats include color names, such as 'blue' and 'red', and hexadecimal colors specified as #RRGGBB
highlightWidth: The width of edges between highlighted nodes. Default is 2
legendColorbar: Logical, whether to add a legend with a color bar for log2 fold changes. Default is TRUE
legendInteraction: Logical, whether to add a legend that links edge types to biological interactions. Default is TRUE
title: The title of the plot. Default is NULL not to include a plot title
titleCex: The cex of the plot main title. Default is 2
titleFace: An integer which specifies which font to use for title. 1 corresponds to plain text, 2 to bold face, 3 to italic, 4 to bold italic, and 5 to symbol font. Default is 1

Value

A base R plot with the augmented pathway.

Details

The network created by this function is highly flexible, allowing to tweak different parameters that can influence the resulting graph, including node highlighting, layout algorithms, colors, and legends.

Nodes included in the plot

For huge messy networks, the user can specify the nodes to include in the plot through the subgraph parameter, in order to represent only the features that he wants to display. Alternatively, this parameter can be set to NULL (default), to plot all nodes of that biological pathway.

Highlight nodes and edges

One interesting feature offered by this function consists in highlighting specific nodes and edges within a network. This results particularly useful when we want to put in evidence affected routes in a biological pathway. To highlight nodes, you must provide the highlightNodes parameter with a character vector that lists all the desired nodes. As a result, the borders of highlighted nodes will be colored according to highlightCol parameter (default is 'gold'), and will have a width specified by highlightWidth (default is 2). Notably, this function automatically highlights in the same way the edges connecting the selected nodes.

Layout algorithms

Furthermore, this function allows to use different methods to lay out nodes in the network by setting the algorithm parameter. In this regard, several algorithms in Rgraphviz package can be used, namely:

dot (default), which is an algorithm attributed to Sugiyama et al. and described by Gansner et al., that creates a ranked layout that is particularly suited to display hierarchies and complex pathways;
circo, which uses a recursive radial algorithm resulting in a circular layout;
fdp, which adopts a force-directed approach similar to that of Fruchterman and Reingold;
neato, which relies on a spring model where an iterative solver finds low energy configurations;
osage, which is a layout engine that recursively draws cluster subgraphs;
twopi, which places a node in the center of the network, and then arranges the remaining nodes in a series of concentric circles around the center.

For additional information on these algorithms, refer to Rgraphviz::GraphvizLayouts.

Customization

To customize the look of the resulting plot, this function allows to change different graphical parameters, including:

the color scale for log2 fold changes, that can be set with lfcScale;
the font size of nodes, which can be changed through fontsize;
the border color for nodes, which can be edited with nodeBorderCol;
the text color of nodes, which can be changed through nodeTextCol;
the color used for edges, set by edgeCol;
the width of edges, customizable with edgeWidth.

Additionally, this function allows to include handy legends that are useful for interpreting the biological consequences of network alterations. In particular:

a color bar legend displaying the log2 fold changes corresponding to each fill color can be included with legendColorbar = TRUE (default); and
a legend that links the appearance of edges and arrow heads to the type of biological interaction can be shown through legendInteraction = TRUE (default).

Lastly, title, titleCex and titleFace parameters can be tweaked to include a network title with the desired look.

Note

This function uses the Rgraphviz package to render the network object.

Author

Jacopo Ronchi, jacopo.ronchi@unimib.it

Examples

# load example IntegrativePathwayAnalysis object
obj <- loadExamples("IntegrativePathwayAnalysis")

# explore a specific biological network
visualizeNetwork(obj, "Thyroid hormone synthesis")