functionalNetwork {FGNet} | R Documentation

## Creates and plots the functional gene network.

### Description

Plots the functional networks.

The default network links genes to genes, or terms to terms. The bipartite network links genes or terms to their clusters.

### Usage

    functionalNetwork(incidMatrices, plotType = c("default", "bipartite")[1],
        plotOutput = "static", plotTitle = "Functional Network",
        plotTitleSub = NULL, legendPrefix = NULL, legendText = NULL,
        geneExpr = NULL, plotExpression = c("border", "fill"),
        vExprColors=c(neg="#008000", zero="white", pos="#FF2020"),
        vSize = 12, vLabelCex = 2/3, vLayout = NULL, keepColors = TRUE,
        bgTransparency = 0.4, eColor = "#323232", eWidth=NULL, weighted = FALSE,
        keepAllNodes = FALSE, plotAllMg = FALSE)

### Arguments

`incidMatrices` | list or matrix. Raw output (list) from `fea2incidMat`: a list with slots: "gtSetsMatrix", "filteredOut" and either "metagroupsMatrix" or "clustersMatrix". If only a matrix is provided, it will be asumed to be the clusters matrix, and all nodes will be connected to every other node in the metagroup.
`plotType` | "default" or "bipartite". Default network: Nodes are either genes or terms. Edges join nodes in common gene-term sets. Background and node color represent cluster/metagroup. White nodes are in several clusters/metagroups. Bipartite network: Nodes are genes or terms (circles) and their clusters (squares). By default it keeps only the genes or terms in more than one cluster or metagroup, which represents a simplified version of the functional network. Node shape is only available in the "static" output.
`plotOutput` | "static", "dynamic" or "none". "static" will generate a standard R plot. "dynamic" will produce an interactive tkplot (metagroups background cannot be drawn). "none" will not plot the network.
`plotTitle` | character. Title to show on the plot.
`plotTitleSub` | character. Text to show at the bottom of the plot (sub-title).
`legendPrefix` | character. Label to show next to the cluster/metagroup id in the legend. In the bipartite network the legens replaces the cluster node label.
`legendText` | character. Description of each cluster (shown as the legend). If FALSE, legend is not shown.
`geneExpr` | numeric. Named vector with the relative expression value of the gene (node). 0 is taken as reference, positive values will be plotted red, negative values green.
`plotExpression` | character. Determines the way to plot the expression: "border" adds a red or green border to the node, "fill" colors the whole with the expression color instead of the metagroup color.
`vExprColors` | character. Vector with the colors for expression: first color for negative values, second for zero, and third for positive.
`vSize` | numeric. Vertex size. If named, it allows to set a value for each gene. Name as "default" to set a default value, otherwise the default value is the mean.
`vLabelCex` | numeric. A numerical value giving the amount by which plotting text and symbols should be magnified relative to the default label size.
`vLayout` | 2 x n matrix or character. Where n is the number of nodes in the graph, each column gives the (x, y)-coordinates for the corresponding node. The bipartite network accepts "kk" (Kamada Kawai), "circle", or "sugiyama" (hierarquical).
`keepColors` | logical. If TRUE, it will keep the same colors for all the plots, independently of the filtered groups. Only available if incidMatrices is the raw result from `fea2incidMat()`.
`bgTransparency` | numeric. Value between 0 and 1 for the transparency of the metagroups background (only default network).
`eColor` | character. Color for the edges.
`eWidth` | numeric. Edge width. Not to plot edges, set eWidth=0 or eColor=NA.
`weighted` | logical. If TRUE, edges width will be based on the number of shared gene-term sets.
`keepAllNodes` | logical. Only used in bipartite network. If FALSE, nodes in only one cluster are not plotted. If TRUE, all nodes in the clusters are shown.
`plotAllMg` | logical. Only used in bipartite network. If FALSE, non-connected clusters are not plotted. If TRUE, all non-filtered clusters are shown.

### Value

Plots the functional networks.

An invisible list with the igraph networks and incidence matrices, to collect it assign it to a variable.

### See Also

Previous step in the workflow: `fea2incidMat()`

To see the terms included in each cluster or metagroup: `getTerms()`

Overview of the package: `FGNet`

Package tutorial: `vignette("FGNet-vignette")`

### Examples

    ###################################################
    # Previous steps
    # Set gene list:
    genesYeast <- c("ADA2", "APC1", "APC11", "APC2", "APC4", "APC5", "APC9",
        "CDC16", "CDC23", "CDC26", "CDC27", "CFT1", "CFT2", "DCP1", "DOC1", "FIP1",
        "GCN5", "GLC7", "HFI1", "KEM1", "LSM1", "LSM2", "LSM3", "LSM4", "LSM5",
        "LSM6", "LSM7", "LSM8", "MPE1", "NGG1", "PAP1", "PAT1", "PFS2", "PTA1",
        "PTI1", "REF2", "RNA14", "RPN1", "RPN10", "RPN11", "RPN13", "RPN2", "RPN3",
        "RPN5", "RPN6", "RPN8", "RPT1", "RPT3", "RPT6", "SGF11", "SGF29", "SGF73",
        "SPT20", "SPT3", "SPT7", "SPT8", "TRA1", "YSH1", "YTH1")
    # Optional gene expression
    genesYeastExpr <- setNames(c(rep(1,29), rep(-1,30)), genesYeast) # 1=UP, -1=DW

    # FEA:
    # jobID <- query_gtLinker(genesYeast, organism = "Sc")
    jobID <- 3907019
    results <- fea_gtLinker_getResults(jobID)

    ###################################################
    # Gene-based networks:
    incidMat <- fea2incidMat(results, filterAttribute="Silhouette Width")

    functionalNetwork(incidMat, geneExpr=genesYeastExpr)
    functionalNetwork(incidMat, plotType="bipartite", plotOutput="dynamic", vSize=c(default=10, GLC7=20, PTA1=20))

    getTerms(results)

    # To modify the layout and plot as static network (with metagroup background)...
    library(igraph)
    # saveLayout <- tkplot.getcoords(1)   # tkp.id (ID of the tkplot window)
    # functionalNetwork(incidMat, vLayout=saveLayout, plotType="bipartite")

    # Only return the network, without plotting
    fNw <- functionalNetwork(incidMat, plotOutput="none")
    class(fNw)
    names(fNw)
    betweenness(fNw$iGraph$commonClusters)

    ###################################################
    # Term-based network
    incidMat_terms <- fea2incidMat(results, key="Terms")
    functionalNetwork(incidMat_terms, weighted=TRUE, plotOutput="dynamic")
    functionalNetwork(incidMat_terms, plotType="bipartite", plotOutput="dynamic",
        plotAllMg=TRUE)
    functionalNetwork(incidMat_terms, plotType="bipartite", plotOutput="dynamic",
        keepAllNodes=TRUE)

    # Including generic terms filterd by GtLinker from final metagroups:
    incidMat_terms2 <- fea2incidMat(results, key="Terms", removeFiltered=FALSE)
    functionalNetwork(incidMat_terms2, weighted=TRUE)

[Package FGNet version 3.14.0 Index]