Description Usage Arguments Details Value Author(s) References See Also Examples
PCSF_rand
returns a union of subnetworks obtained by solving the PCSF on the
given interaction network by adding a random noise to edge costs each time.
1 | PCSF_rand(ppi, terminals, n = 10, r = 0.1, w = 2, b = 1, mu = 5e-04)
|
ppi |
An interaction network as an igraph object. |
terminals |
A list of terminal genes with prizes to be analyzed in the PCSF context.
A named |
n |
An |
r |
A |
w |
A |
b |
A |
mu |
A |
In order to increase the robustness of the resulting structure, it is recommended to solve the PCSF several times on the same network while adding some noise to the edge costs each time, and combine all results in a final subnetwork. The union of all outputs may explain the underlying biology better.
The final subnetwork obtained by taking the union of the PCSF outputs generated by adding a random noise to edge costs each time. It returns an igraph object with the node prize and edge cost attributes representing the total number of show ups throughout all runs.
Murodzhon Akhmedov
Akhmedov M., LeNail A., Bertoni F., Kwee I., Fraenkel E., and Montemanni R. (2017) A Fast Prize-Collecting Steiner Forest Algorithm for Functional Analyses in Biological Networks. Lecture Notes in Computer Science, to appear.
1 2 3 4 5 6 7 8 | ## Not run:
library("PCSF")
data("STRING")
data("Tgfb_phospho")
terminals <- Tgfb_phospho
ppi <- construct_interactome(STRING)
subnet <- PCSF_rand(ppi, terminals, n = 10, r =0.1, w = 2, b = 2, mu = 0.0005)
## End(Not run)
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