View source: R/evaluateCorrDecay.R

plotCorrDecay | R Documentation |

Plot correlation delay using subsampling

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

`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 |

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

```
library(GenomicRanges)
library(ggplot2)
data('decorateData')
# Evaluate hierarchical clustering
treeList = runOrderedClusteringGenome( simData, simLocation )
# Evaluate how correlation between features decays with distance
dfDist = evaluateCorrDecay( treeList, simLocation )
# make plot
plotCorrDecay( dfDist )
```

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