Visualizing small RNA complexity

library(igraph)

These two data frames contain information about edges and counts

# first column: vertex1; second column: vertex2
head(tls)
##   V1   V2
## 1  1 1443
## 2  1  868
## 3  1 3623
## 4  1  790
## 5  1 2206
## 6  2 3624
# first column: vertex name; second column: counts-expression
head(c)
##   V1      V2
## 1  1  542607
## 2  2   17963
## 3  3 1624431
## 4  4  227791
## 5  5  154312
## 6  6    7198

And the result is the following network. Red indicates low expresison, and yellow, high expression.Each vertex is a location, and edges show locations sharing all or some sRNAs.

c$col <- cut(log2(c$V2), breaks = c(-1, 12, 15, 23), labels = heat.colors(3))
g <- graph.data.frame(tls, directed = F, vertices = c)
plot(g, layout = layout.fruchterman.reingold, vertex.color = V(g)$col, vertex.size = 2, 
    vertex.label = NA, edge.arrow.size = 0.3, vertex.frame.color = V(g)$col)

plot of chunk unnamed-chunk-4