Hi all,
I have a data set of two postions on the genome with a third value for number of interactions. I would like to plot this data set so I can see how many interactions are on each position.
the data set looks like that (this is only a subset of the complete, very long list):
partner1 partner2 Interactions
1 10001 11
1 15001 1
1 20001 1
1 25001 4
1 30001 8
5001 20001 1
5001 40001 3
5001 45001 15
5001 50001 1
10001 15001 3
10001 20001 3
10001 25001 6
10001 30001 12
15001 70001 2
15001 90001 6
15001 95001 5
15001 100001 1
20001 4195001 30
20001 4200001 62
20001 4205001 81
20001 4210001 3
25001 30001 5
25001 40001 22
25001 45001 13
4200001 4210001 318
4200001 4215001 2
4205001 4210001 308
4205001 4215001 2
4210001 4215001 1
i would like to have the column 'partner1' on the x-axis, the column 'partner2' on the y-axis and the number of interactions (3rd column) in the plot with the option to have there either a point, the number itself of a colored gradient like in the heatmaps.
Does anyone know of an R package for creating such plots, or for that matter, any other way of doing it?
thanks
Assa
I have tried with ggplot.
require(ggplot2)
pl1 <- ggplot(subset, aes(y = factor(partner1), x = factor(partner2))) + geom_tile(aes(fill = Interactions)) + scale_fill_continuous(low = "blue", high = "green") + scale_size(range = c(1, 200))
With the small subset I get a similar plot to the one you posted. But with the complete data set I get a different picture:
Is there a simple explanation for that? Does the order of the columns of the two partner columns make a difference?
That still didn't change anything. I still get the plot on only half of the window. I can't figure why, as I have for both columns the same amount of factors (842 vs. 843).
is it possible to make the legend a bit more comprehensive? I won't to have more than just 5 different categories. I need a much bigger separation - something like 20 or 25 different color points.
What about this...
## Dummy data
dat<- data.frame(partner1= 1:100, partner1= 1:100, Interactions= 1:100)
ncols<- length(unique(dat$Interactions))<br />
cols<- data.frame(<br />
colour= colorRampPalette(c("blue", "red"))(ncols),
Interactions= sort(unique(dat$Interactions)), stringsAsFactors= FALSE)
dat<- merge(dat, cols)
## Unocmment to Make colour transparent, it might look better
#trasp<- '80'
#dat$colour<- paste(dat$colour, trasp, sep= '')
## Plot symbol
plot(x= dat$partner1, y= dat$partner2, pch= 19, col= dat$colour, cex= 2)
## As text
plot(x= dat$partner1, y= dat$partner2, type= 'n')
text(x= dat$partner1, y= dat$partner2, labels= dat$Interactions, col= dat$colour, cex= 0.5)
I'm going to use the "pheatmap" package to draw a heatmap of your data. with the code below I generate a matrix from your dataframe so that it can be used as an argument for pheatmap.
library(pheatmap)
names<-unique(c(data[,1], data[,2]))
mat<-matrix(data=0, nrow=length(names), ncol=length(names))
rownames(mat)<-sort(names)
colnames(mat)<-sort(names)
for (i in 1:nrow(data))
{
partner1 <- as.character(data[i,1])
partner2 <- as.character(data[i,2])
interactions <- data[i,3]
mat[partner1, partner2] <- interactions
}
pheatmap(mat, cluster_cols=F, cluster_rows=F)
•
written
by
t.candelli
A good solution to such a problem is to draw a network representation where:
- partners are nodes
- column 3 is the thickness of the link
THE SOFT for that is Cytoscape
I would use a circle plot and have the ribbon thickness represent the strength of the interaction.
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I think the best way to represent this sort of data would be with a heatmap. is there a directionality between partner one and partner 2? e.g. the values
1 5000 8are different from5000 1 8in your tableyes there is a difference. The information on the two partner columns are genomic positions. So it make a difference whether the first or the second partner is on a specific position. Doesn't it?
How would you put the data into a heatmap?