How can I construct a gene co-expression network in R from the expression value I have in Excel sheet?

Please tell me what packages are the helpful or share any tutorial for the construction of the co-expression network in R.

Thank you

Construct gene coexpression network

0

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2.1 years ago

How can I construct a gene co-expression network in R from the expression value I have in Excel sheet?

Please tell me what packages are the helpful or share any tutorial for the construction of the co-expression network in R.

Thank you

3

Entering edit mode

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)
```

0

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Hi F I used your commands for my data but after "weight.matrix <- GENIE3(mycounts)" I got error:

```
Error in (function (classes, fdef, mtable) :
unable to find an inherited method for function ‘GENIE3’ for signature ‘"data.frame"
```

my data are log2 of FPKM and I have -INF in some rows, could you help? Thanks

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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.