show_cn_group_profile: Show Summary Copy Number Profile for Sample Groups

In sigminer: Extract, Analyze and Visualize Mutational Signatures for Genomic Variations

Show Summary Copy Number Profile for Sample Groups

Description

Show Summary Copy Number Profile for Sample Groups

Usage

show_cn_group_profile(
  data,
  groups = NULL,
  fill_area = TRUE,
  cols = NULL,
  chrs = paste0("chr", c(1:22, "X")),
  genome_build = c("hg19", "hg38", "T2T", "mm10", "mm9", "ce11"),
  cutoff = 2L,
  resolution_factor = 1L,
  force_y_limit = TRUE,
  highlight_genes = NULL,
  repel = FALSE,
  nrow = NULL,
  ncol = NULL,
  return_plotlist = FALSE
)

Arguments

data	a CopyNumber object or a data.frame containing at least 'chromosome', 'start', 'end', 'segVal', 'sample' these columns.
groups	a named list or a column name for specifying groups.
fill_area	default is TRUE, fill area with colors.
cols	length-2 colors for AMP and DEL.
chrs	chromosomes start with 'chr'.
genome_build	genome build version, used when data is a data.frame, should be 'hg19' or 'hg38'.
cutoff	copy number value cutoff for splitting data into AMP and DEL. The values equal to cutoff are discarded. Default is 2, you can also set a length-2 vector, e.g. c(2, 2).
resolution_factor	an integer to control the resolution. When it is 1 (default), compute frequency in each cytoband. When it is 2, use compute frequency in each half cytoband.
force_y_limit	default is TRUE, force multiple plots
highlight_genes	gene list to highlight. have same y ranges. You can also set a length-2 numeric value.
repel	if TRUE (default is FALSE), repel highlight genes to avoid overlap.
nrow	number of rows in the plot grid when multiple samples are selected.
ncol	number of columns in the plot grid when multiple samples are selected.
return_plotlist	default is FALSE, if TRUE, return a plot list instead of a combined plot.

Value

a (list of) ggplot object.

Examples

load(system.file("extdata", "toy_copynumber.RData",
  package = "sigminer", mustWork = TRUE
))

p1 <- show_cn_group_profile(cn)
p1

ss <- unique(cn@data$sample)
p2 <- show_cn_group_profile(cn, groups = list(a = ss[1:5], b = ss[6:10]))
p2
p3 <- show_cn_group_profile(cn,
  groups = list(g1 = ss[1:5], g2 = ss[6:10]),
  force_y_limit = c(-1, 1), nrow = 2
)
p3

## Set custom cutoff for custom data
data <- cn@data
data$segVal <- data$segVal - 2L
p4 <- show_cn_group_profile(data,
  groups = list(g1 = ss[1:5], g2 = ss[6:10]),
  force_y_limit = c(-1, 1), nrow = 2,
  cutoff = c(0, 0)
)
p4

## Add highlight gene
p5 <- show_cn_group_profile(cn, highlight_genes = c("TP53", "EGFR"))
p5

sigminer documentation built on May 29, 2024, 3:11 a.m.