Launches a Shiny app to visualise the data and fitted models of a cpam object

Usage

visualise(
  cpo,
  subset = NULL,
  degs_only = TRUE,
  deg_threshold = 0.05,
  p_type = c("p_gam", "p_mvn"),
  shape_type = c("shape1", "shape2")
)

Arguments

cpo: A cpam object containing count data, model fits, and optional changepoint/shape estimates
subset: Character vector; names of targets or genes (if cpo$gene_level = TRUE) to load into the Shiny app. If NULL, all genes/targets are included based on degs_only.
degs_only: Logical; if TRUE, display only differentially expressed genes/targets with adjusted p-value below deg_threshold. Default is TRUE.
deg_threshold: Numeric; significance threshold for differentially expressed genes/targets. Only used when degs_only = TRUE. Default is 0.05.
p_type: character; choose the type of p-value. Options are "p_gam" (default) or "p_mvn" (see compute_p_values() for details).
shape_type: character; "shape1" to include unconstrained or otherwise "shape2". Default is "shape1". In some instances, all of the transcripts for a gene may be "null" shaped, but the p-value for the gene may still be significant. This is due to the different methods of determining significance for the changepoints and the gene-level p-values. Here, conservatively, we remove these null-shaped genes from the DEG list.

Value

None (launches Shiny app in browser)

Examples

if (interactive()){

# A simple gene-level example
cpo <- cpo_example

# Launch visualization with all genes
visualise(cpo, degs_only = FALSE)

# Launch with only significant genes
visualise(cpo, deg_threshold = 0.05)

# Launch with specific genes
visualise(cpo, subset = c("g001","g002","g003"))
}