Plot fitted changepoint additive models

Usage

plot_cpam(
  cpo,
  gene_id = NULL,
  target_id = NULL,
  cp_type = c("cp_1se", "cp_min"),
  shape_type = "shape1",
  bs = "auto",
  cp_fix = -1,
  facet = FALSE,
  sp = NULL,
  show_fit = TRUE,
  show_data = TRUE,
  show_fit_ci = TRUE,
  show_data_ci = TRUE,
  ci_prob = "se",
  remove_null = FALSE,
  null_threshold = 0.05,
  null_threshold_adj = TRUE,
  k_mult = 1.2,
  return_fits_only = FALSE,
  family = "nb",
  common_y_scale = TRUE,
  scaled = FALSE,
  base_size = 12
)

Arguments

cpo: A cpam object containing count data, model fits, and optional changepoint/shape estimates
gene_id: character; gene_id (mutually exclusive with target_id)
target_id: character; target_id (mutually exclusive with gene_id)
cp_type: One of "cp_1se" or "cp_min"; rule for selecting changepoint from fitted models. See estimate_changepoint() for details.
shape_type: One of "shape1" or "shape2"; which set of fitted shape patterns to use. See select_shape() for details.
bs: Shape pattern to fit ("null", "lin", "ilin", "dlin", or from cpo$bss). Use "auto" (default) to use estimated shapes as per shape_type.
cp_fix: Numeric; fixed changepoint time. Set to -1 (default) to use estimated changepoints
facet: Logical; for multiple transcripts, plot in separate facets?
sp: numerical; set the smooth parameter. NULL (default) for automatic selection
show_fit: logical; show the fitted trend?
show_data: logical; show (possibly normalized and scaled) data points?
show_fit_ci: logical; show credible interval for the fitted trend?
show_data_ci: logical; show bootstrapped quantile for data points?
ci_prob: "se" for standard error bands (see mgcv::predict.gam()), or numeric for simulation-based intervals. If numerical, sets the probability for the simulation-based estimates of credible interval.
remove_null: logical; only plot differentially expressed transcripts (not applicable for gene-only analyses)
null_threshold: numeric; P value threshold for filtering out NULL transcripts
null_threshold_adj: logical; use adjusted (default) or non-adjusted p-values for filtering targets
k_mult: numerical; multiplier for the number of knots in the spline. Not recommended to change this value.
return_fits_only: logical; return the model fits. Does not plot the function
family: character; negative binomial ("nb", default) or Gaussian ("gaussian")
common_y_scale: logical; for faceted plots of multiple transcripts, should the scale of the y-axis be common or free.
scaled: logical; scaled data by overdispersions (for bootstrapped data only)
base_size: numeric; base font size for the plot

Value

a ggplot object

Details

Plots the fitted trend and data points for a given gene or target. If a gene ID is supplied, the function will plot all transcripts for that gene. The function can also be used to return the model fit(s) only, which are gamObject objects from the mgcv package.

Examples

library(cpam)

# load gene-only example cpam object
load(system.file("extdata", "cpo_example.rda", package = "cpam"))

# example gene
plot_cpam(cpo_example, gene_id = "g003")


# gene with estimated changepoint at timepoint 3
plot_cpam(cpo_example, gene_id = "g013")


# manually set the changepoint
plot_cpam(cpo_example, gene_id = "g013", cp_fix = 2)