singleplot: Plot an absolute copy number profile for a single sample

In tgac-vumc/ACE: Absolute Copy Number Estimation from Low-coverage Whole Genome Sequencing

Plot an absolute copy number profile for a single sample

Description

singleplot is the core plotting function of ACE. Input can be either a template or a QDNAseq-object with the index of the sample specified. Several of the arguments are parameters obtained from model fitting. Returns a ggplot2 graph with absolute copies on the y-axis and genomic position on the x-axis.

Usage

singleplot(template, QDNAseqobjectsample = FALSE, 
  cellularity = 1, error, ploidy = 2, standard, title, 
  trncname = FALSE, cap = 12, bottom = 0, chrsubset, 
  onlyautosomes = TRUE, sgc = c())

Arguments

template	Object. Either a data frame as created by objectsampletotemplate, or a QDNAseq-object
QDNAseqobjectsample	Integer. Specifies which sample to analyze from the QDNAseq-object. Required when using a QDNAseq-object as template. Default = FALSE
cellularity	Numeric. Used for rescaling bin and segment values. Printed on graph. Default = 1
error	Numeric. When given, it is printed on the graph below cellularity.
ploidy	Integer. Assume the median of segments has this absolute copy number. Default = 2
standard	Numeric. Force the given ploidy to represent this raw value. When omitted, the standard will be calculated from the data. When using parameters obtained from squaremodel, specify standard = 1
title	Character string. Overwrites the automatically generated title
trncname	Logical. In case of a QDNAseq object, the name of the sample is retrieved from the object and used as title. If set to TRUE, trncname truncates the sample name from the first instance of "_" in the name. You can also specify the regular expression here, e.g. trncname = "-.*" truncates the name from the first dash. Default = FALSE
cap	Integer. Influences your output copy number graphs. The upper limit of the y-axis is set at this number. When set to "max", it sets the cap to the maximum absolute copynumber value, rounded up. Bins and segments that exceed the cap are represented by a special mark. Recommended use between 8 and 16. Default = 12
bottom	Integer. Similar to cap, but for the lower limit of the y-axis. When set to "min", it sets the bottom to the minimum absolute copynumber value, rounded down. Bins and segments that subceed the bottom are represented by a special mark. Default = 0
chrsubset	Integer vector. Specify the chromosomes you want to plot. It will always take the full range of chromosomes in your subset, so specifying chrsubset = c(4, 8) will give the same plot as chrsubset = 4:8. When using a subset, singleplot will not plot the cellularity and error on the plot. Therefore, you can use this to make a copy number plot without this information by specifying chrsubset = 1:22
onlyautosomes	Logical or integer. You can fill in an integer to specify how many autosomes your species has. When TRUE, singleplot defaults to 22 (human) autosomes. When FALSE, singleplot will also plot whichever other chromosomes are specified in the template, e.g. "X", "Y", "MT". You can combine this argument with chrsubset, for instance chrsubset[1:23] to only include chromosome X (provided this is the 23rd chromosome)
sgc	Integer or character vector. Specify which chromosomes occur with only a single copy in the germline

Value

Returns a graph generated through the ggplot2 package.

Note

singleplot expects chromosome names, as specified in the chr column of the template, to be either just the integer chromosome number, or "chr" followed by the chromosome number. This is strictly required when onlyautosomes = TRUE.

When plotting sex chromosomes, make sure to specify sgc = c() when plotting the copy number profile of a male individual.

Author(s)

Jos B. Poell

See Also

objectsampletotemplate, squaremodel, singlemodel

Examples

## simulated data assuming each chromosome comprises 100 bins
s <- jitter(c(1, 1, 0.8, 1.2, rep(1, 5), 1.4, rep(1, 13)), amount = 0)
n <- c(100, 100, 40, 60, rep(100, 5), 100, rep(100, 13))
bin <- 1:2200
chr <- rep(1:22, each = 100)
start <- rep(0:99*1000000+1, 22)
end <- rep(1:100*1000000, 22)
copynumbers <- jitter(rep(s,n), amount = 0.05)
segments <- rep(s, n)
template <- data.frame(bin = bin, chr = chr, start = start, end = end, 
  copynumbers = copynumbers, segments = segments)
model <- singlemodel(template)
bestfit <- model$minima[model$rerror==min(model$rerror)]
singleplot(template, cellularity = tail(bestfit, 1), title = "sim")

## using segmented data from a QDNAseq-object
data("copyNumbersSegmented")
singlemodel(copyNumbersSegmented, QDNAseqobjectsample = 1)
singleplot(copyNumbersSegmented, QDNAseqobjectsample = 1, 
  cellularity = 0.79)
## QDNAseq 'blacklists' sex chromosomes, but singleplot can plot them
singleplot(copyNumbersSegmented, QDNAseqobjectsample = 1, 
  cellularity = 0.79, chrsubset = 12:24, onlyautosomes = FALSE)

tgac-vumc/ACE documentation built on Nov. 29, 2022, 12:15 a.m.