Reading your normalized gene expression data in r which has been saved as .txt and genes are in rows and samples are in columns

```
mycounts <- read.table("data.txt", header = T, sep = "\t",row.names = 1)
# watching the head of uploaded file
head(mycounts[,1:4])
# watching the dimension of matrix
dim(mycounts)
```

Using this R package for instance, you must put your working directory in where `gene3.R`

and your expression files are. You must also install these packages in R that all help you to illustrate your network in Cytoscape. Download `geneie3.R`

source from this link clicking on R/randomForest part

```
library(GENIE3)
library(igraph)
library(RCy3)
library(Rgraphviz)
weight.matrix <- GENIE3(mycounts)
link.list <- linkList(weight.matrix, report.max=1000)
edge_listsi <- link.list[!duplicated(link.list),]
Gsi <- graph.data.frame(edge_listsi,directed = F)
Asi <- get.adjacency(Gsi,sparse = F,attr = "weight",type = "both")
g_arasi <- graph.adjacency(Asi,mode = "undirected",weighted = T)
g.cyto <- igraph.to.graphNEL(g_arasi)
cw = createNetworkFromGraph("net", graph=g.cyto)
displayGraph (cw)
```

•

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modified 13 months ago
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written
22 months ago by
A • **3.7k**
Please show some effort of trying. Post input data, and expected output? At the least post some links to published papers. As it stands this post is too broad and unclear.

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