Scatterplots Showing Correlation Between Gene Pairs

Question

[spaul8505]

I have two dataframes

 x<-data.frame(matrix(rnorm(1000), nrow=1000, ncol=10))
 y<-data.frame(matrix(rnorm(1000), nrow=1000, ncol=10))

where the rows are the genes and the columns are samples. I wanted to produce a scatterplot showing the correlation between all gene-pairs in " x" (x-axis) relative to the correlation of the same gene in "y" (y-axis).

I transposed the dataframes to calculate gene corrleations and adopted the following code to produce the scatterplot:

 x<-t(x)
 y<-t(y)  

  DF <- data.frame(x,y)

 # Calculate 2d density over a grid
 library(MASS)
 dens <- kde2d(x,y)

 # create a new data frame of that 2d density grid
 gr <- data.frame(with(dens, expand.grid(x,y)), as.vector(dens$z))
 names(gr) <- c("xgr", "ygr", "zgr")

# Fit a model
 mod <- loess(zgr~xgr*ygr, data=gr)

# Apply the model to the original data to estimate density at that point DF$pointdens <- predict(mod, newdata=data.frame(xgr=x, ygr=y))

# Draw plot
library(ggplot2)
ggplot(DF, aes(x=x,y=y, color=pointdens)) + geom_point() +scale_colour_gradientn(colours =  rainbow(5)) + theme_bw()

But when I apply the following code to my transposed data, I get the error

(list) object cannot be coerced to type 'double'

The plot am trying to produce look similar to this

Are there other ways to do this?

Answer 1

[Irsan]

What you want to do is to plot an all-vs-all correlation matrix plot. There is a package called GGally that takes as input your matrix with genes as rows and columns as samples, calculates all the possible sample-vs-samples correlations and plots it with ggplot2. When you install it, make sure your R version is up to date, GGally depends on R version > 3.0

Answer 2

[UnivStudent]

You might also want to try using the stat_density2d function in ggplot2. It seems like it might be a simpler way of doing this. Probably would save you the trouble of doing this yourself with the 2d density. There are some good examples in the documentation which I've linked.