netModule: Identifying miRNA sponge modules from network

In zhangjunpeng411/miRspongeR: Identification and analysis of miRNA sponge regulation

Identifying miRNA sponge modules from network

Description

Identifying miRNA sponge modules from network. Possible methods include FN, MCL, LINKCOMM, MCODE, betweenness, infomap, prop, eigen, louvain, walktrap.

Usage

netModule(spongenetwork, method = "MCL", directed = FALSE, modulesize = 3, save = FALSE)

Arguments

spongenetwork	Input miRNA sponge interaction network.
method	Cluster method, can select one of FN, MCL, LINKCOMM, MCODE, betweenness, infomap, prop, eigen, louvain, walktrap.
directed	A logical value, the network is directed or not.
modulesize	The size cutoff of the identified modules.
save	A logical value, save the identified modules or not.

Value

A list of miRNA sponge modules.

Author(s)

Junpeng Zhang (https://www.researchgate.net/profile/Junpeng_Zhang3)

References

1. Clauset A, Newman ME, Moore C. Finding community structure in very large networks. Phys Rev E Stat Nonlin Soft Matter Phys., 2004, 70(6 Pt 2):066111.

2. Enright AJ, Van Dongen S, Ouzounis CA. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res., 2002, 30(7):1575-84.

3. Kalinka AT, Tomancak P. linkcomm: an R package for the generation, visualization, and analysis of link communities in networks of arbitrary size and type. Bioinformatics, 2011, 27(14):2011-2.

4. Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics, 2003, 4:2.

5. Newman ME, Girvan M. Finding and evaluating community structure in networks. Phys Rev E Stat Nonlin Soft Matter Phys. 2004;69(2 Pt 2):026113.

6. Rosvall M, Bergstrom CT. Maps of random walks on complex networks reveal community structure. Proc Natl Acad Sci U S A. 2008;105(4):1118-1123.

7. Raghavan UN, Albert R, Kumara S. Near linear time algorithm to detect community structures in large-scale networks. Phys Rev E Stat Nonlin Soft Matter Phys. 2007;76(3 Pt 2):036106.

8. Newman ME. Finding community structure in networks using the eigenvectors of matrices. Phys Rev E Stat Nonlin Soft Matter Phys. 2006;74(3 Pt 2):036104.

9. Blondel VD, Guillaume JL, Lambiotte R, Lefebvre E. Fast unfolding of communities in large networks. Journal of statistical mechanics: theory and experiment, 2008, 2008(10): P10008.

10. Pons P, Latapy M. Computing communities in large networks using random walks. Graph Algorithms Appl. 2006.

Examples

# Obtain miRNA-target interaction data file "miR2Target.csv" in csv format
miR2Target <- system.file("extdata", "miR2Target.csv", package="miRspongeR")
miRTarget <- read.csv(miR2Target, header=TRUE, sep=",")
miRHomologyceRInt <- spongeMethod(miRTarget, method = "miRHomology")
spongenetwork_Cluster <- netModule(miRHomologyceRInt[, 1:2])

zhangjunpeng411/miRspongeR documentation built on Aug. 26, 2024, 6:48 a.m.