#### modify moduleSim moduleVisual readGR shannon splitn summarize and checkOK

Mingsheng Zhang authored on 02/12/2018 21:01:39
Showing 1 changed files
 ... ... @@ -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, 42 +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) 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) 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) 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)] <- 52 52  t(correlation.m)[lower.tri(correlation.m)] 53 53   54 54  matrix.v<-matrix(0.5,5,12) 55 55  matrix.v<-as.data.frame(matrix.v) 56 -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))) 60 -module.topology=epihet::moduleVisual(correlation.m, 60 +module.topology<-epihet::moduleVisual(correlation.m, 61 61  value.matrix=matrix.v, 62 62  moduleColors=modulecolor, 63 63  mymodule="yellow",cutoff=0.02,

#### revised all R/*.R, rerun roxygenize(), check successed

Mingsheng Zhang authored on 21/11/2018 13:04:47
Showing 1 changed files
 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} 4 +\alias{moduleVisual} 5 +\title{Modules visualization and network topology} 6 +\usage{ 7 +moduleVisual(TOM, value.matrix, moduleColors, mymodule, cutoff = 0.02, 8 + prefix = NULL, sve = FALSE) 9 +} 10 +\arguments{ 11 +\item{TOM}{the topological overlap matrix in WGCNA generated from 12 +the epiNetwork() function} 13 + 14 +\item{value.matrix}{A data frame generated from the epiNetwork() function. 15 +the row name is patients in one subtype. the column name is the DEH loci 16 +the value in the matrix is epigenetic heterogeneity on one DEH loci 17 +for one patient} 18 + 19 +\item{moduleColors}{the module assignment generated from the epiNetwork() 20 +function} 21 + 22 +\item{mymodule}{a character vector containing the module colors 23 +you want to visulaize} 24 + 25 +\item{cutoff}{adjacency threshold for including edges in the output (default:0.02)} 26 + 27 +\item{prefix}{a character for output filename} 28 + 29 +\item{sve}{A boolean to save the plot (default: FALSE)} 30 +} 31 +\value{ 32 +a list containing all module edge and node information for mymodule 33 +} 34 +\description{ 35 +Visualize the modules identified by epiNetwork() function, and calculate 36 +network topology 37 +} 38 +\examples{ 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, 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, 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) 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) 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)] = 52 +t(correlation.m)[lower.tri(correlation.m)] 53 + 54 +matrix.v<-matrix(0.5,5,12) 55 +matrix.v<-as.data.frame(matrix.v) 56 +colnames(matrix.v)=c("NM_052960","NR_138250","NM_015074","NM_183416", 57 +"NM_017891","NM_001330306","NM_014917","NM_001312688","NM_001330665", 58 +"NM_017766","NM_001079843","NM_001040709") 59 +modulecolor<-c(rep(c("yellow","cyan"),c(10,2))) 60 +module.topology=epihet::moduleVisual(correlation.m, 61 + value.matrix=matrix.v, 62 + moduleColors=modulecolor, 63 + mymodule="yellow",cutoff=0.02, 64 + prefix='CEBPA_sil_epipoly',sve = TRUE) 65 +}