Plot quantification at multiple levels — plot_protein

For the exploration of specific proteins, it's often useful to visualise the quantification at multiple levels, e.g PSM, peptide, filtered peptides and protein. This function plots the quantitative data at multiple levels (assays) for a given list of proteins of interest.

Usage

plot_protein_assays(
  obj,
  poi,
  experiments_to_plot = NULL,
  protein_id_col = "Master.Protein.Accessions",
  label_col = "Master.Protein.Accessions",
  rename_labels = NULL,
  log2transform_cols = "",
  norm_quant = FALSE,
  add_mean_summary = FALSE,
  colour_assays = FALSE,
  alpha_assays = TRUE
)

Arguments

obj: QFeatures object
poi: list. Proteins of interest
experiments_to_plot: list. experiments (assays) to plot. Defaults to all assays
protein_id_col: string. Column with the protein ids to search for poi values
label_col: string. Column with labels to use for proteins in plot
rename_labels: named list. Mapping from labels to renamed labels
log2transform_cols: list. Assays which need to be log2-transforms (all values should ultimately be transformed)
norm_quant: logical. Should the quantifications be normalised to the fold-change vs mean abundance
add_mean_summary: logical. Add a line summarising the mean value over all features in the assay (Not recommended if norm_quant=FALSE)
colour_assays: logical. Column each assay
alpha_assays: logical. Set sensible alpha value for each assay

Value

ggplot object.