plotCNEWidth {CNEr} | R Documentation

## Plot the CNE widths distribution

### Description

CNE widths can follow heavy tailed distribution that are associated with power-laws. This function plots the reverse cumulative density distribution of CNE widths, and fits a discrete power-law distribution. Goodness of fit can also be evaluated.

### Usage

      plotCNEWidth(x, ...)

### Arguments

`x` | `GRangePairs` object: a pair of CNEs.
`...` | Additional points passed to `plot` function.

### Details

The power-law distribution is associated with heavy tailed distribution.

A reverse cumulative density distribution plot will be generated with optimal lower bound xmin, scaling parameteralpha for power-law fit.

### Value

An invisible list of fitted model is returned.

### Note

The power-law distribution implementation is based on the poweRlaw package.

### Author(s)

Ge Tan

### References

Salerno, W., Havlak, P., and Miller, J. (2006). Scale-invariant structure of strongly conserved sequence in genomic intersections and alignments. Proc. Natl. Acad. Sci. U.S.A. 103, 13121-13125.

### Examples

      dbName <- file.path(system.file("extdata", package="CNEr"),
                          "danRer10CNE.sqlite")
      cneGRangePairs <- readCNERangesFromSQLite(dbName=dbName,
                                                tableName="danRer10_hg38_45_50")
      plotCNEWidth(cneGRangePairs)

[Package CNEr version 1.20.0 Index]