Description Usage Arguments Details Value Author(s) See Also Examples
A function to create an igraph
object from a ScudoResults
object. In the graph, nodes
are samples and edges quantify the similarity between the nodes.
1 | scudoNetwork(object, N, colors = character())
|
object |
a |
N |
a number between 0 and 1, representing the fraction of the signature-to-signature distances that will be used to draw the graph |
colors |
a character vector of hexadecimal RGB color codes used to color
the nodes of the graph. |
This function uses the distance matrix in the
ScudoResults
object to generate an
igraph
object, representing a graph
where nodes are samples and edges quantify the similarity between the
signatures of pairs of nodes.
The distance matrix in object
is used to generate an unweighted
adjacency matrix, that is then used to generate the graph. The sample
quantile of probability N, computed from all the non-zero distances in the
distance matrix, is used as a threshold to generate the adjacency matrix: all
the distances larger than this quantile are mapped to 0, all the distances
smaller than this quantile are mapped to 1 (with the exception of the
distances of any node from itself, which are equal to 0).
Distances are set as attributes of the edges. Use
igraph::E(igraphObject)$distance
to retrieve them, where
igraphObject
is the result of scudoNetwork
.
The color
parameter controls the color of the nodes. It must be a
vector of hexadecimal RGB color codes (like "#FFFFFF"
), with length
equal to
the number of samples in object
. By default, a different color is
assigned to each group. If no group is specified in object
, all nodes
are set to the same color. A vector of node colors can be accessed
with igraph::V(igraphObject)$color
. Use
igraph::V(igraphObject)$group
to access the group label of each node
(it returns NULL if no group is specified in object
).
An object of class igraph
.
Matteo Ciciani matteo.ciciani@gmail.com, Thomas Cantore cantorethomas@gmail.com
scudoCytoscape
, ScudoResults
,
igraph
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | # generate dummy dataset and run scudo
exprData <- data.frame(a = 11:20, b = 16:25,
c = rev(1:10), d = c(1:2, rev(3:10)))
rownames(exprData) <- letters[11:20]
grps <- as.factor(c("G1", "G1", "G2", "G2"))
nTop <- 2
nBottom <- 3
res <- scudoTrain(exprData, grps, nTop, nBottom, foldChange = FALSE,
featureSel = FALSE)
# generate network
col <- c("#FF0000", "#FF0000", "#0000FF", "#0000FF")
net <- scudoNetwork(res, N = 0.5, colors = col)
# retrieve node colors and groups
nodes <- igraph::V(net)
colors <- nodes$color
groups <- nodes$group
# retrieve distances from edges
edges <- igraph::E(net)
dist <- edges$distance
# plot the network
scudoPlot(net)
|
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