miRSM_SS: miRSM_SS

In zhangjunpeng411/miRSM: Inferring miRNA sponge modules in heterogeneous data

miRSM_SS

Description

Inferring sample-specific miRNA sponge modules

Usage

miRSM_SS(
  Modulelist.all,
  Modulelist.exceptk,
  sim.cutoff = 0.8,
  sim.method = "Simpson"
)

Arguments

Modulelist.all	List object, modules using all of samples.
Modulelist.exceptk	List object, modules using all of samples excepting sample k.
sim.cutoff	Similarity cutoff between modules, the interval is [0 1].
sim.method	Methods for calculating similatiry between two modules, select one of three methods (Simpson, Jaccard and Lin). Default method is Simpson.

Value

A list of sample-specific miRNA sponge modules

Author(s)

Junpeng Zhang (https://www.researchgate.net/profile/Junpeng-Zhang-2)

Examples

data(BRCASampleData)
nsamples <- 3
modulegenes_all <- module_igraph(ceRExp[, 151:300], mRExp[, 151:300])
modulegenes_exceptk <- lapply(seq(nsamples), function(i) 
                              module_WGCNA(ceRExp[-i, seq(150)], 
                              mRExp[-i, seq(150)]))
 
miRSM_SRVC_all <- miRSM(miRExp, ceRExp[, 151:300], mRExp[, 151:300], 
                        miRTarget, modulegenes_all, 
                        method = "SRVC", SMC.cutoff = 0.01, 
                        RV_method = "RV")
miRSM_SRVC_exceptk <- lapply(seq(nsamples), function(i) miRSM(miRExp[-i, ], 
                             ceRExp[-i, seq(150)], mRExp[-i, seq(150)], 
                             miRTarget, modulegenes_exceptk[[i]],                                     
                             method = "SRVC",
                             SMC.cutoff = 0.01, RV_method = "RV"))

Modulegenes_all <- miRSM_SRVC_all[[2]]
Modulegenes_exceptk <- lapply(seq(nsamples), function(i) 
                              miRSM_SRVC_exceptk[[i]][[2]])

Modules_SS <- miRSM_SS(Modulegenes_all, Modulegenes_exceptk)

zhangjunpeng411/miRSM documentation built on Sept. 23, 2024, 4:37 a.m.