HMMcopy Visualization {HMMcopy} | R Documentation

## Visualization functions for correctReadcount results

### Description

Convinience functions for creating plots for the analysis of the readcount correction process by `correctReadcount`

### Usage

    plotBias(correctOutput, points = 10000, ...)
    plotCorrection(correctOutput, chr = space(correctOutput)[1], ...)
    plotSegments(correctOutput, segmentOutput, chr = space(correctOutput)[1], ...)
    plotParam(segmentOutput, param, ...)
    stateCols()

### Arguments

`correctOutput` | Output value from `correctReadcount`
`segmentOutput` | Output value from `HMMsegment`
`points` | Number of random sampled points to plot, decreasing reduces runtime
`chr` | Chromosome name to plot. A single value for `plotCorrection` and a vector for `plotSegments`.
`param` | Input parameters to call that produced segmentOutput
`...` | Furthur arguments are passed to `plot`.

### Details

`plotBias` shows the effects of the correction process on GC bias and mappability bias in HTS readcounts.

`plotCorrection` shows the effects of the correction on the copy number profile. Defaultly plotting the entire first chromosome found in the list.

`plotSegments` shows the resultant segments and states assigned to each segment.

`plotParam` shows the initial suggested distribution of copy number in each state (dashed), and the optimal distribution of copy number in each state (solid)

`stateCols` returns a vector of six colours used in `plotSegments` and `plotParam`

### Author(s)

Daniel Lai

### See Also

`correctReadcount` and `HMMsegment` for generating intended output.

### Examples

    data(tumour)

    # Visualize one at a time
    par(ask = TRUE)
    plotBias(normal_copy)
    plotCorrection(tumour_copy)
    par(mfrow = c(1, 1))
    plotSegments(tumour_copy, tumour_segments)
    plotParam(tumour_segments, tumour_param)

[Package HMMcopy version 1.22.0 Index]