| pathway | R Documentation |
An S4 class to represent a gene-gene interaction network
pathway is the pathway object constructor.
show displays the pathway object briefly
summary generates a pathway object summary including basic network properties.
pathway2igraph converts a pathway object into an
igraph object with edge attribute sign
analyze pathway network properties
get_genes is a helper function that extracts the gene names in a
pathway and returns a vector containing character
elements of gene names
plot visualizes the pathway as igraph object
sample_genes randomly selects effect gene in a
pathway according the betweenness centrality and (no -1) neighors
pathway(object, ...)
## S4 method for signature 'ANY'
pathway(id, adj = matrix(0), sign = NULL)
## S4 method for signature 'pathway'
show(object)
## S4 method for signature 'pathway'
summary(object)
## S4 method for signature 'pathway'
pathway2igraph(object)
## S4 method for signature 'pathway'
analyze(object, ...)
## S4 method for signature 'pathway'
get_genes(object)
## S4 method for signature 'pathway,missing'
plot(
x,
y = NA,
highlight.genes = NULL,
gene.names = c(NULL, "legend", "nodes"),
main = NULL,
asp = 0.95,
vertex.size = 11,
vertex.color = "khaki1",
vertex.label.cex = 0.8,
edge.width = 2,
edge.color = "olivedrab4",
...
)
## S4 method for signature 'pathway'
sample_genes(object, no = 3)
object |
An object of class |
... |
Further arguments can be added to the function. |
id |
A |
adj |
A |
sign |
A |
x |
|
y |
missing (placeholder) |
highlight.genes |
vector of gene names or node id's, which should be highlighted in a different color, default is |
gene.names |
character indicating whether the genes names should appear in a legend ( |
main |
optional overall main title, default is |
asp |
a |
vertex.size |
a |
vertex.color |
a |
vertex.label.cex |
a |
edge.width |
a |
edge.color |
a |
no |
a |
pathway2igraph returns an unweighted igraph object with edge attribute sign
analyze returns a data.frame consisting of
pathway id,
number of genes,
number of links,
number of inhibition links,
network density,
average degree,
average degree of inhibition links,
network diamter,
transitivity, and
signed transitivity (Kunegis et al., 2009).
get_genes returns a character vector of gene names extracted from adjacency matrix rownames.
sample_genes returns a vector of length no with
vertex id's of sampled genes
analyze(pathway):
get_genes(pathway):
sample_genes(pathway):
idA character repesenting the pathway id,
e.g. hsa00100 as used in the KEGG database.
adjA matrix respresenting the network adjacency matrix of dimension
equaling the number of genes (1 interaction, 0 otherwise)
signA numeric vector indicating the interaction type for
each link (1 activation, -1 inhibition) in the interaction network for the
pathway.
Juliane Manitz, Stefanie Friedrichs, Patricia Burger
Details to the computation and interpretation can be found in:
Kolaczyk, E. D. (2009). Statistical analysis of network data: methods and models. Springer series in statistics. Springer.
Kunegis, J., A. Lommatzsch, and C. Bauckhage (2009). The slashdot zoo: Mining a social network with negative egdes. In Proceedings of the 18th international conference on World wide web, pp. 741-750. ACM Press.
# pathway object constructor
pathway(id="hsa04022")
# convert to igraph object
data(hsa04020)
str(hsa04020)
g <- pathway2igraph(hsa04020)
str(g)
# analyze pathway network properties
data(hsa04020)
summary(hsa04020)
analyze(hsa04020)
# extract gene names from pathway object
get_genes(hsa04020)
# plot pathway as igraph object
plot(hsa04020)
sample3 <- sample_genes(hsa04020, no = 3)
plot(hsa04020, highlight.genes = sample3)
# sample effect genes
sample3 <- sample_genes(hsa04020, no = 3)
plot(hsa04020, highlight.genes = sample3)
sample5 <- sample_genes(hsa04020, no = 5)
plot(hsa04020, highlight.genes = sample5)
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