networkPlot | R Documentation |
Draws a network with gene sets as nodes and the thickness of the edges correlating to the number of shared genes. The gene set significance is visualized as color intensities. Gives an overview of the influence of overlap on significant gene sets.
networkPlot( gsaRes, class, direction, adjusted = FALSE, significance = 0.001, geneSets = NULL, overlap = 1, lay = 1, label = "names", cexLabel = 0.9, ncharLabel = 25, cexLegend = 1, nodeSize = c(10, 40), edgeWidth = c(1, 15), edgeColor = NULL, scoreColors = NULL, main )
gsaRes |
an object of class |
class |
a character string determining the p-values of which
directionality class that should be used as significance information for the
plot. Can be one of |
direction |
a character string giving the direction of regulation, can
be either |
adjusted |
a logical, if adjusted p-values should be used, or not. Note
that if |
significance |
the significance cut-off that determines which gene sets are included in the plot. Defaults to 0.001. |
geneSets |
a character vector of gene set names, to be included in the
plot. Defaults to |
overlap |
a positive numerical. Determines the smallest number of sharing genes between two gene-sets that is needed in order to draw a line/edge between the gene-sets. Defaults to 1. |
lay |
a numerical between 1-5, or a layout function (see
|
label |
a character string, either |
cexLabel |
the text size of the node labels. |
ncharLabel |
the number of characters to include in the node labels. |
cexLegend |
the text size of the legend. |
nodeSize |
a numerical vector of length 2 giving the maximum and minimum node sizes. The node size represents the size of the gene set, and all values will be scaled to the given interval. |
edgeWidth |
a numerical vector of length 2 giving the maximum and minimum edge widths. The edge width represents the number of shared genes between two gene sets, and all values will be scaled to the given interval. |
edgeColor |
a character vector giving the colors to use for increasing edge width. Can also be set to a single color. Defaults to a gray-scale. |
scoreColors |
a character vector giving the colors from which the
gradient used for node coloring will be created. In the case of
|
main |
an optional character vector setting the title of the plot. |
In the case of class="distinct"
and direction="both"
, the
distinct directional p-values (pDistinctDirUp
and
pDistinctDirDn
, see runGSA
) will be used in
combination. Using the geneSets
and lay
arguments, multiple
comparative plots (i.e. with the same layout) can be drawn, based for
instance on the output gene set list from other network plots with different
directionality classes.
Returns a list with two components: geneSets
containing the
names and numbers of the gene sets in the plot, and layout
,
containing the saved layout of the plot, which can be passed back to the
lay
argument in order to draw a subsequent plot with the same layout.
Leif Varemo piano.rpkg@gmail.com and Intawat Nookaew piano.rpkg@gmail.com
piano, runGSA
, GSAheatmap
,
networkPlot2
, exploreGSAres
,
layout
# Load example input data to GSA: data("gsa_input") # Load gene set collection: gsc <- loadGSC(gsa_input$gsc) # Run gene set analysis: gsares <- runGSA(geneLevelStats=gsa_input$pvals , directions=gsa_input$directions, gsc=gsc, nPerm=500) # Network plot: networkPlot(gsares,class="non",significance=0.01) # Use circular layout and save the layout: nw <- networkPlot(gsares,class="non",significance=0.01,lay=5) # Use the saved layout to overlay the distinct-directional p-values for easy comparison. # Note that the gene sets are now not selected based on a significance cutoff, but from a list: networkPlot(gsares,class="distinct",direction="both",lay=nw$layout,geneSets=nw$geneSets)
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