plot_with_fitting_curve {proBatch}R Documentation

Plot peptide measurements across multi-step analysis

Description

Plot Intensity of a few representative peptides for each step of the analysis including the fitting curve

Usage

plot_with_fitting_curve(pep_name, df_long, sample_annotation, fit_df,
  fit_value_var = "fit", order_col = "order",
  sample_id_col = "FullRunName", batch_col = "MS_batch",
  measure_col = "Intensity", feature_id_col = "peptide_group_label",
  geom = c("point", "line"), color_by_batch = FALSE,
  color_scheme = "brewer", facet_by_batch = FALSE,
  plot_title = sprintf("Fitting curve of %s peptide", pep_name),
  color_by_col = NULL, color_by_value = NULL, theme = "classic",
  vline_color = "grey", ...)

Arguments

pep_name

name of the peptide for diagnostic profiling

df_long

data frame where each row is a single feature in a single sample. It minimally has a sample_id_col, a feature_id_col and a measure_col, but usually also an m_score (in OpenSWATH output result file)

sample_annotation

data matrix with:

  1. sample_id_col (this can be repeated as row names)

  2. biological covariates

  3. technical covariates (batches etc)

fit_df

data frame typically output generated from nonlinear curve fitting by normalize_custom_fit

fit_value_var

column denoting intensity values, typically fitted to curve

order_col

column in sample_annotation that determines sample order. It is used for certain diagnostics and normalisations.

sample_id_col

name of the column in sample_annotation file, where the filenames (colnames of the data matrix are found)

batch_col

column in sample_annotation that should be used for batch comparison

measure_col

if df_long is among the parameters, it is the column with expression/abundance/intensity; otherwise, it is used internally for consistency

feature_id_col

name of the column with feature/gene/peptide/protein ID used in the long format representation df_long. In the wide formatted representation data_matrix this corresponds to the row names.

geom

for the intensity measure_col profile

color_by_batch

(logical) whether to color points by batch

color_scheme

color scheme for ggplot representation

facet_by_batch

(logical) whether to plot each batch in its own facet

plot_title

the string indicating the source of the peptides

color_by_col

column to color by certain value denoted by color_by_value

color_by_value

value in color_by_col to color

theme

plot theme (default is 'classical'; other options not implemented)

vline_color

color of vertical lines, typically denoting different MS batches in ordered runs; should be NULL for experiments without intrinsic order

...

additional arguments to plot_single_feature function

Value

ggplot-class plot with minimally two facets (before and after non-linear fit) with measure_col (Intensity) vs order_col (injection order) for selected peptides (specified in pep_name)

See Also

Other feature-level diagnostic functions: plot_iRT, plot_peptides_of_one_protein, plot_single_feature, plot_spike_in

Examples

loess_fit_70 <- adjust_batch_trend(example_proteome_matrix, 
example_sample_annotation, span = 0.7)

fitting_curve_plot <- plot_with_fitting_curve(
pep_name = "10231_QDVDVWLWQQEGSSK_2", 
df_long = example_proteome, example_sample_annotation, 
fit_df = loess_fit_70$fit_df, plot_title = "Curve fitting with 70% span")


[Package proBatch version 1.0.0 Index]