How to enlarge a section of y-axis? I am using ggplot2 to plot a scatter plot.

library(ggforce) # required by facet_zoom

g &lt;- ggplot(data.plot, aes(x = Methyl_Average, y = Average_Gene_Expression))  
g1 &lt;-  g + geom_point(color = "steelblue") + theme_bw(base_family = "Times") +
       ggtitle( "Scatter Plot") + 
       theme_bw(base_family = "Times") +
       theme(plot.title = element_text(hjust = 0.5))    




As most of my data points are in the range of 0 - 200 on y-axis, I want to zoom this section. I tried doing it using facet_zoom from ggforce package :

g1 + facet_zoom(y = Average_Gene_Expression &gt; 0 &amp; Average_Gene_Expression &lt; 200)    




Instead of two plots in one figure, I want one plot (like first figure), where 80% of y-axis displays the data points in the range of 0 - 200 and 20% of the y-axis displays the remaining and x-axis unaltered. Which function/package should I use do it in R?
I would strongly discourage you from making discontinuous axis, it's going to be very confusing for a reader. 

The facet plot you proposed seems like a good solution to me. Alternatively you can use log transformation. To demonstrate I made it on simulated data that look appox like yours :

set.seed(940401)

data.plot &lt;- data.frame(Methyl_Average = c(0.05, rbeta(699, 2, 5) + 0.15, runif(300, 0.18, 0.85)),
                        Average_Gene_Expression = c(165, exp(rnorm(999, 3))))

library(ggplot2)
require(gridExtra)

g &lt;- ggplot(data.plot, aes(x = Methyl_Average, y = Average_Gene_Expression))
g1 &lt;-  g + geom_point(color = "steelblue") + theme_bw(base_family = "Times") +
       ggtitle( "Scatter Plot") +
       theme_bw(base_family = "Times") +
       theme(plot.title = element_text(hjust = 0.5))

sc_plot &lt;- g1 +
           labs(x = "Differential Methylation", y = "Differential Expression")
logsc_plot &lt;- g1 + 
              labs(x = "Differential Methylation", y = "Differential Expression (log10 scale)") + 
              scale_y_continuous(trans='log10')

grid.arrange(sc_plot, logsc_plot, ncol = 2)