qc_ranked_intensities function

Check ranked intensities

Calculates and plots ranked intensities for proteins, peptides or precursors.

qc_ranked_intensities(
  data,
  sample,
  grouping,
  intensity_log2,
  facet = FALSE,
  plot = FALSE,
  y_axis_transformation = "log10",
  interactive = FALSE
)

Arguments

• data: a data frame that contains at least sample names, grouping identifiers (precursor, peptide or protein) and log2 transformed intensities for each grouping identifier.
• sample: a character column in the data data frame that contains the sample names.
• grouping: a character column in the data data frame that contains protein, precursor, or peptide identifiers.
• intensity_log2: a numeric column in the data data frame that contains the log2 transformed intensities of the selected grouping variable.
• facet: a logical value that specifies whether the calculation should be done group wise by sample and if the resulting plot should be faceted by sample. (default is FALSE). If facet = FALSE the median of each protein intensity will be returned.
• plot: a logical value that specifies whether the result should be plotted (default is FALSE).
• y_axis_transformation: a character value that determines that y-axis transformation. The value is either "log2" or "log10" (default is "log10").
• interactive: a logical value that specifies whether the plot should be interactive (default is FALSE).

Returns

A data frame containing the ranked intensities is returned. If plot = TRUE a plot is returned. The intensities are log10 transformed for the plot.

Examples

set.seed(123) # Makes example reproducible

# Create synthetic data
data <- create_synthetic_data(
  n_proteins = 50,
  frac_change = 0.05,
  n_replicates = 4,
  n_conditions = 3,
  method = "effect_random",
  additional_metadata = FALSE
)

# Plot ranked intensities for all samples combined
qc_ranked_intensities(
  data = data,
  sample = sample,
  grouping = peptide,
  intensity_log2 = peptide_intensity,
  plot = TRUE,
)

# Plot ranked intensities for each sample separately
qc_ranked_intensities(
  data = data,
  sample = sample,
  grouping = peptide,
  intensity_log2 = peptide_intensity,
  plot = TRUE,
  facet = TRUE
)