Plotting peptide in whole provided sequence
This function takes the quantified peptide data frame and plots the matched peptide sequences in the provided whole sequence. The function returns a ggplot object that visually represents the matched peptide sequences in the context of the entire sequence, allowing for comprehensive analysis and visualization.
Users have the flexibility to customize the presentation of sequences, deciding whether to separate them in the display. This can be achieved using the facet_nested function from ggplot2, which organizes sequences into distinct columns. For instance, users can separate heavy chain (HC) and light chain (LC) regions for major sequence categories by specifying them in the x_axis_vars parameters of the function. By default, facet_nested introduces spacing to ensure clear visual separation between facets. However, users can adjust these spaces through theme settings in ggplot2, using parameters like panel.spacing and strip.background to control the separation between subplots.
To maintain sequence continuity, users can define domains using a domain table, which enables the annotation of specific domains such as VH, CH1, CH2, CH3, VL, and CL. This approach ensures that continuous sequences are accurately depicted without unnecessary breaks, providing precise visual cues for domain boundaries.
# Plotting peptide in whole provided sequence
domain <- data.frame(
domain_type = c("VH", "CH1", "CH2", "CH3", "VL", "CL", "CDR H1", "CDR H2", "CDR H3", "CDR L1", "CDR L2", "CDR L3"),
Chain = c("HC", "HC", "HC", "HC", "LC", "LC", "HC", "HC", "HC", "LC", "LC", "LC"),
Epitope = c("Boco", "Boco", "Boco", "Boco", "Boco", "Boco", "Boco", "Boco", "Boco", "Boco", "Boco", "Boco"),
domain_start = c(1, 119, 229, 338, 1, 108, 26, 50, 97, 24, 50, 89),
domain_end = c(118, 228, 337, 444, 107, 214, 35, 66, 107, 34, 56, 97),
domain_color = c("black", "black", "black", "black", "black", "black", "#F8766D", "#B79F00", "#00BA38", "#00BFC4", "#619CFF", "#F564E3"),
domain_fill_color = c("white", "white", "white", "white", "white", "white", "yellow", "yellow", "yellow", "yellow", "yellow", "yellow"),
domain_label_y = c(1.7, 1.7, 1.7, 1.7, 1.7, 1.7, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4)
)
x_axis_vars <- c("Chain")
y_axis_vars <- c("Donor")
column_order <- list(
Donor = "D1,D2,D3,D4,D5,D6,D7,D8",
Chain = "HC,LC"
)
PTM_color <- c(
"Ox" = "red",
"Deamid" = "cyan",
"Cam" = "blue",
"Acetyl" = "magenta"
)
label_filter = list(Donor = "D1")
p_psm <- create_peptide_plot(
data_with_psm,
y_axis_vars,
x_axis_vars,
y_expand = c(0.2, 0.2),
x_expand = c(0.5, 0.5),
theme_options = list(legend.box = "horizontal", legend.position = "bottom"),
labs_options = list(title = "PSM Plot", x = "Position", fill = "PSM"),
color_fill_column = 'PSM',
fill_gradient_options = list(), # Set the limits for the color scale
label_size = 1.3,
add_domain = TRUE,
domain = domain,
domain_start_column = "domain_start",
domain_end_column = "domain_end",
domain_type_column = "domain_type",
domain_border_color_column = "domain_color",
domain_fill_color_column = "domain_fill_color",
add_domain_label = TRUE,
domain_label_size = 2,
domain_label_y_column = "domain_label_y",
domain_label_color = "black",
PTM = TRUE,
PTM_type_column = "PTM_type",
PTM_color = PTM_color,
add_label = TRUE,
label_column = "Character",
label_filter = label_filter,
label_y = 1,
column_order = column_order
)
print(p_psm)
# Launching the Shiny App
You can interactively explore your data and visualization options using the built-in Shiny application provided by PepMapViz. Simply run the following command in your R console to launch the app.
PepMapViz::run_pepmap_app()