...  ... 
@@ 37,27 +37,27 @@ network topology 
37  37 
} 
38  38 
\examples{ 
39  39 
correlation.m<matrix(0,12,12) 
40 
correlation.m[1,c(2:10)]=c(0.006,0.054,0.079,0.078, 0.011,0.033,0.014, 

40 
+correlation.m[1,c(2:10)]<c(0.006,0.054,0.079,0.078, 0.011,0.033,0.014, 

41  41 
0.023,0.034) 
42 
correlation.m[2,c(3:10)]=c(0.026,0.014,0.045,0.037, 0.026,0.011,0.034, 

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+correlation.m[2,c(3:10)]<c(0.026,0.014,0.045,0.037, 0.026,0.011,0.034, 

43  43 
0.012) 
44 
correlation.m[3,c(4:10)]=c(0.016,0.024,0.039,0.045, 0.009,0.003,0.028) 

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correlation.m[4,c(5:10)]=c(0.039,0.002,0.053,0.066, 0.012,0.039) 

46 
correlation.m[5,c(6:10)]=c(0.019,0.016,0.047,0.046, 0.013) 

47 
correlation.m[6,c(7:10)]=c(0.017,0.057,0.029,0.056) 

48 
correlation.m[7,c(8:10)]=c(0.071,0.018,0.001) 

49 
correlation.m[8,c(9:10)]=c(0.046,0.014) 

50 
correlation.m[9,10]=0.054 

51 
correlation.m[lower.tri(correlation.m)] = 

44 
+correlation.m[3,c(4:10)]<c(0.016,0.024,0.039,0.045, 0.009,0.003,0.028) 

45 
+correlation.m[4,c(5:10)]<c(0.039,0.002,0.053,0.066, 0.012,0.039) 

46 
+correlation.m[5,c(6:10)]<c(0.019,0.016,0.047,0.046, 0.013) 

47 
+correlation.m[6,c(7:10)]<c(0.017,0.057,0.029,0.056) 

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+correlation.m[7,c(8:10)]<c(0.071,0.018,0.001) 

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+correlation.m[8,c(9:10)]<c(0.046,0.014) 

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+correlation.m[9,10]<0.054 

51 
+correlation.m[lower.tri(correlation.m)] < 

52  52 
t(correlation.m)[lower.tri(correlation.m)] 
53  53 

54  54 
matrix.v<matrix(0.5,5,12) 
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matrix.v<as.data.frame(matrix.v) 
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colnames(matrix.v)=c("NM_052960","NR_138250","NM_015074","NM_183416", 

56 
+colnames(matrix.v)<c("NM_052960","NR_138250","NM_015074","NM_183416", 

57  57 
"NM_017891","NM_001330306","NM_014917","NM_001312688","NM_001330665", 
58  58 
"NM_017766","NM_001079843","NM_001040709") 
59  59 
modulecolor<c(rep(c("yellow","cyan"),c(10,2))) 
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module.topology=epihet::moduleVisual(correlation.m, 

60 
+module.topology<epihet::moduleVisual(correlation.m, 

61  61 
value.matrix=matrix.v, 
62  62 
moduleColors=modulecolor, 
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mymodule="yellow",cutoff=0.02, 
1  1 
new file mode 100644 
...  ... 
@@ 0,0 +1,65 @@ 
1 
+% Generated by roxygen2: do not edit by hand 

2 
+% Please edit documentation in R/moduleVisual.R 

3 
+\name{moduleVisual} 

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+\alias{moduleVisual} 

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+\title{Modules visualization and network topology} 

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+\usage{ 

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+moduleVisual(TOM, value.matrix, moduleColors, mymodule, cutoff = 0.02, 

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+ prefix = NULL, sve = FALSE) 

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+} 

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+\arguments{ 

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+\item{TOM}{the topological overlap matrix in WGCNA generated from 

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+the epiNetwork() function} 

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+ 

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+\item{value.matrix}{A data frame generated from the epiNetwork() function. 

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+the row name is patients in one subtype. the column name is the DEH loci 

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+the value in the matrix is epigenetic heterogeneity on one DEH loci 

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+for one patient} 

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+ 

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+\item{moduleColors}{the module assignment generated from the epiNetwork() 

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+function} 

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+ 

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+\item{mymodule}{a character vector containing the module colors 

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+you want to visulaize} 

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+ 

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+\item{cutoff}{adjacency threshold for including edges in the output (default:0.02)} 

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+ 

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+\item{prefix}{a character for output filename} 

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+ 

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+\item{sve}{A boolean to save the plot (default: FALSE)} 

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+} 

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+\value{ 

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+a list containing all module edge and node information for mymodule 

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+} 

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+\description{ 

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+Visualize the modules identified by epiNetwork() function, and calculate 

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+network topology 

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+} 

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+\examples{ 

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+correlation.m<matrix(0,12,12) 

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+correlation.m[1,c(2:10)]=c(0.006,0.054,0.079,0.078, 0.011,0.033,0.014, 

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+0.023,0.034) 

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+correlation.m[2,c(3:10)]=c(0.026,0.014,0.045,0.037, 0.026,0.011,0.034, 

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+0.012) 

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+correlation.m[3,c(4:10)]=c(0.016,0.024,0.039,0.045, 0.009,0.003,0.028) 

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+correlation.m[4,c(5:10)]=c(0.039,0.002,0.053,0.066, 0.012,0.039) 

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+correlation.m[5,c(6:10)]=c(0.019,0.016,0.047,0.046, 0.013) 

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+correlation.m[6,c(7:10)]=c(0.017,0.057,0.029,0.056) 

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+correlation.m[7,c(8:10)]=c(0.071,0.018,0.001) 

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+correlation.m[8,c(9:10)]=c(0.046,0.014) 

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+correlation.m[9,10]=0.054 

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+correlation.m[lower.tri(correlation.m)] = 

52 
+t(correlation.m)[lower.tri(correlation.m)] 

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+ 

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+matrix.v<matrix(0.5,5,12) 

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+matrix.v<as.data.frame(matrix.v) 

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+colnames(matrix.v)=c("NM_052960","NR_138250","NM_015074","NM_183416", 

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+"NM_017891","NM_001330306","NM_014917","NM_001312688","NM_001330665", 

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+"NM_017766","NM_001079843","NM_001040709") 

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+modulecolor<c(rep(c("yellow","cyan"),c(10,2))) 

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+module.topology=epihet::moduleVisual(correlation.m, 

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+ value.matrix=matrix.v, 

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+ moduleColors=modulecolor, 

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+ mymodule="yellow",cutoff=0.02, 

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+ prefix='CEBPA_sil_epipoly',sve = TRUE) 

65 
+} 