Description Usage Arguments Value Examples
Visualize the modules identified by epinetwork() function.
1 2 | modulevisual(TOM, value.matrix, moduleColors, mymodule, cutoff = 0.02,
prefix = NULL, sve = FALSE)
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TOM |
the topological overlap matrix in WGCNA generated from the network.construct() function |
value.matrix |
A data frame generated from the epinetwork() function. the row name is patients in one subtype. the column name is the DEH loci the value in the matrix is epigenetic heterogeneity on one DEH loci for one patient |
moduleColors |
the module assignment generated from the epinetwork() function |
mymodule |
a character vector containing the module colors you want to visulaize |
cutoff |
adjacency threshold for including edges in the output. |
prefix |
a character for outpuf filename |
sve |
A boolean to save the plot (default: FALSE) |
a list containing all module edge and node information for mymodule
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | correlation.m<-matrix(0,12,12)
correlation.m[1,c(2:10)]=c(0.006,0.054,0.079,0.078, 0.011,0.033,0.014,
0.023,0.034)
correlation.m[2,c(3:10)]=c(0.026,0.014,0.045,0.037, 0.026,0.011,0.034,
0.012)
correlation.m[3,c(4:10)]=c(0.016,0.024,0.039,0.045, 0.009,0.003,0.028)
correlation.m[4,c(5:10)]=c(0.039,0.002,0.053,0.066, 0.012,0.039)
correlation.m[5,c(6:10)]=c(0.019,0.016,0.047,0.046, 0.013)
correlation.m[6,c(7:10)]=c(0.017,0.057,0.029,0.056)
correlation.m[7,c(8:10)]=c(0.071,0.018,0.001)
correlation.m[8,c(9:10)]=c(0.046,0.014)
correlation.m[9,10]=0.054
correlation.m[lower.tri(correlation.m)] =
t(correlation.m)[lower.tri(correlation.m)]
matrix.v<-matrix(0.5,5,12)
colnames(matrix.v)=c("NM_052960","NR_138250","NM_015074","NM_183416",
"NM_017891","NM_001330306","NM_014917","NM_001312688","NM_001330665",
"NM_017766","NM_001079843","NM_001040709")
modulecolor<-c(rep(c("yellow","cyan"),c(10,2)))
module.topology=epihet::modulevisual(correlation.m,
value.matrix=matrix.v,
moduleColors=modulecolor,
mymodule="yellow",cutoff=0.02,
prefix='CEBPA_sil_epipoly',sve = TRUE)
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