plotPrecursors: Plots features (e.g. Precursor.Id) across entire batch run

In alzel/proteomicsQC: A set of Routines to plot and analyse DIA-NN reports

Plots features (e.g. Precursor.Id) across entire batch run

Description

Plots features (e.g. Precursor.Id) across entire batch run

Usage

plotPrecursors(
  report,
  metadata,
  Q_THR,
  n = 6,
  run_order_var = "run_order",
  feature_var = "Precursor.Id",
  feature_value = "Precursor.Quantity",
  qc_pattern = ".*?QC.*?",
  subtitle = "TEST",
  seed = 123
)

Arguments

metadata	experiment description to arrange by run_order output from create_metadata
qc_pattern	QC file pattern, default: ".*?QC.*?"
subtitle	a string for a plot's subtitle
report	DIA-NN report file
Q_THR	Q-value filtering threshold, default: 0.01
feature_value	feature value to plot, default: "Precursor.Quantity"
feature_var	feature variable, default: "Precursor.Id"
run_order_var	variable for sample running order, default: "run_order"
n	number of features to plot, default: 6

Value

returns feature plot

Examples

metadata <- create_metadata(diann_report)
plotPrecursors(diann_report, metadata = metadata, Q_THR = 0.01, n = 6, run_order_var = "run_order", feature_var="Precursor.Id", feature_value = "Precursor.Quantity", qc_pattern = ".*?MSQC.*?")

alzel/proteomicsQC documentation built on Aug. 11, 2022, 5:58 p.m.