HMMcopy-visualize: Visualization functions for correctReadcount results

In HMMcopy: Copy number prediction with correction for GC and mappability bias for HTS data

Description

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

Usage

plotBias(correctOutput, points = 10000, ...)
plotCorrection(correctOutput, chr = correctOutput$chr[1], ...)
plotSegments(correctOutput, segmentOutput, chr = correctOutput$chr[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)

HMMcopy documentation built on Nov. 8, 2020, 8:09 p.m.