Description Usage Arguments Details Value Author(s) References See Also
A clique based algorithm to identify disease modules from differentially expressed genes originally by Bader et al
1 2 3 | mod_mcode(MODifieR_input, ppi_network, hierarchy = 1, vwp = 0.5,
haircut = F, fluff = F, fdt = 0.8, loops = T,
deg_cutoff = 0.05, module_cutoff = 3.5, dataset_name = NULL)
|
MODifieR_input |
A MODifieR input object produced by one of the |
ppi_network |
A network as a dataframe where the first 2 columns are the interactions |
hierarchy |
This parameter indicates how many hierarchy are included in the network, currently it can be |
vwp |
Vertex weight percentage. Default value is 0.5. |
haircut |
Boolean value, whether to remove singly-connected nodes from clusters (TRUE) or not (FALSE). |
fluff |
Boolean value, whether to spand cluster cores by one neighbour shell outwards (TRUE) or not (FALSE). |
fdt |
Cluster density cutoff. Default value is 0.8. |
loops |
Boolean value, whether to include self-loops (TRUE) or not (FALSE). |
deg_cutoff |
p-value cutoff for differentialy expressed genes |
module_cutoff |
Minimal score for a module to be returned |
dataset_name |
Optional name for the input object that will be stored in the settings object. Default is the variable name of the input object |
Much of the code an documentation has been taken from the now defunct package "ProNet"
mcode returns a list of objects of class "MODifieR_module" with subclass "Mcode". The objects are named lists containing the following components:
module_genes |
A character vector containing the genes in the final module |
module_scores |
A numeric value that denotes the score of the module. Higher is better |
settings |
A named list containing the parameters used in generating the object |
DIrk de Weerd
Bader, G. D., & Hogue, C. W. (2003). An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics, 4(1), 2. https://doi.org/10.1186/1471-2105-4-2
https://github.com/cran/ProNet
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