Plot correlation delay

Plot correlation delay using subsampling

Usage

plotCorrDecay(
  dfDist,
  method = c("R", "Rsq"),
  xlim = c(10, 1e+06),
  n = 100,
  outlierQuantile = 0.001,
  densityExponent = 0.25
)

Arguments

dfDist

data.frame of distance and correlation from from evaluateCorrDecay()

method

on show either R or Rsq on y-axis

xlim

min and max values for x-axis

n

the number of equally spaced points at which the density is to be estimated.

outlierQuantile

show points if density is less than this quantile

densityExponent

color based on density^densityExponent

Details

Plot correlation versus log10 distance. Sample equal number of points for each bin along the x-axis.

Examples

library(GenomicRanges)
library(ggplot2)

data('decorateData')

# Evaluate hierarchical clustering
treeList = runOrderedClusteringGenome( simData, simLocation ) 
#> 
Evaluating:chr20          
#> 

# Evaluate how correlation between features decays with distance
dfDist = evaluateCorrDecay( treeList, simLocation )
#> 
chr20      
#> 

# make plot
plotCorrDecay( dfDist )
#> Scale for y is already present.
#> Adding another scale for y, which will replace the existing scale.
#> Scale for x is already present.
#> Adding another scale for x, which will replace the existing scale.
#> Warning: Removed 23 rows containing non-finite values (`stat_density2d()`).
#> `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
#> Warning: Removed 23 rows containing non-finite values (`stat_smooth()`).
#> Warning: Removed 396 rows containing missing values (`geom_tile()`).
#> Warning: Removed 15 rows containing missing values (`geom_point()`).