Nothing
R/replicates.R
In HaDeX2: Analysis and Visualisation of Hydrogen/Deuterium Exchange Mass Spectrometry Data
Defines functions
show_peptide_mass_measurement
plot_peptide_mass_measurement
Documented in
plot_peptide_mass_measurement
show_peptide_mass_measurement
#' Plot peptide mass measurement
#'
#' @description Plot the mass measurements
#' from replicates for peptide in specific time point.
#'
#' @importFrom ggplot2 geom_vline annotate
#'
#' @param dat data produced by
#' \code{\link{read_hdx}} function
#' @param protein chosen protein
#' @param state biological state for chosen protein
#' @param sequence sequence of chosen peptide
#' @param show_charge_values \code{logical}, indicator if the data
#' is shown for replicates or for charge values within the
#' replicates
#' @param time_t chosen time point
#' @param interactive \code{logical}, whether plot should have an interactive
#' layer created with with ggiraph, which would add tooltips to the plot in an
#' interactive display (HTML/Markdown documents or shiny app)
#'
#' @details This function shows the measurements of mass from
#' different replicates for specific peptide in specific state
#' in specific time point of measurement on the plot.
#' Moreover, on the plot is shown the average mass from the
#' replicates, used later in calculations. The ribbon next to the
#' dotted average mass indicates the uncertainty.
#'
#' @return a [ggplot2::ggplot()] object.
#'
#' @seealso
#' \code{\link{read_hdx}}
#' \code{\link{calculate_exp_masses_per_replicate}}
#' \code{\link{calculate_exp_masses}}
#' \code{\link{calculate_state_uptake}}
#' \code{\link{calculate_diff_uptake}}
#'
#' @examples
#' plot_peptide_mass_measurement(alpha_dat, sequence = "FGSDDEEESEEAKRLRE")
#' plot_peptide_mass_measurement(alpha_dat, sequence = "FGSDDEEESEEAKRLRE", show_charge_values = FALSE)
#'
#' @export plot_peptide_mass_measurement
plot_peptide_mass_measurement <- function(dat,
protein = dat[["Protein"]][1],
state = dat[["State"]][1],
sequence = dat[["Sequence"]][1],
show_charge_values = TRUE,
time_t = unique(dat[["Exposure"]])[3],
interactive = getOption("hadex_use_interactive_plots")){
rep_mass_dat <- calculate_exp_masses_per_replicate(dat)
## temporarly, for compability
rep_mass_dat <- data.table(rep_mass_dat)
dat <- data.table(dat)
##
rep_mass_dat <- rep_mass_dat[Protein == protein & State == state & Sequence == sequence & Exposure == time_t]
avg_value <- mean(rep_mass_dat[["avg_exp_mass"]])
err_avg <- sd(rep_mass_dat[["avg_exp_mass"]])
if(show_charge_values){
rep_mass_z_dat <- dat[Protein == protein & State == state & Sequence == sequence & Exposure == time_t]
rep_mass_z_dat[, `:=`(exp_mass = Center*z - z*1.00727647,
weighted_Inten = scale(Inten))]
if(interactive){
pep_mass_plot <- ggplot() +
geom_point_interactive(data = rep_mass_z_dat, aes(x = exp_mass, y = File, color = as.factor(z), size = weighted_Inten,
tooltip = glue("{Sequence}
Position: {Start}-{End}
Value: {round(exp_mass, 2)},
Replicate: {File}"
))) +
geom_point_interactive(data = rep_mass_dat, aes(x = avg_exp_mass, y = File,
tooltip = glue("{Sequence}
Position: {Start}-{End}
Value: {round(avg_exp_mass, 2)},
Replicate: {File}")), size = 3) +
geom_vline(xintercept = avg_value, color = "red", linetype = "dashed", linewidth = 1.5) +
annotate("rect",
xmin = avg_value - err_avg, xmax = avg_value + err_avg,
ymin = -Inf, ymax = Inf, fill = "red", alpha=.03) +
labs(y = "",
x = "Measured mass [Da]",
title = paste0("Peptide ", sequence, " in state ", state, " in ", time_t, " min"),
color = "Charge",
size = "rel Inten") +
theme(legend.direction = "vertical")
} else {
pep_mass_plot <- ggplot() +
geom_point(data = rep_mass_z_dat, aes(x = exp_mass, y = File, color = as.factor(z), size = weighted_Inten)) +
geom_point(data = rep_mass_dat, aes(x = avg_exp_mass, y = File), size = 3) +
geom_vline(xintercept = avg_value, color = "red", linetype = "dashed", linewidth = 1.5) +
annotate("rect",
xmin = avg_value - err_avg, xmax = avg_value + err_avg,
ymin = -Inf, ymax = Inf, fill = "red", alpha=.03) +
labs(y = "",
x = "Measured mass [Da]",
title = paste0("Peptide ", sequence, " in state ", state, " in ", time_t, " min"),
color = "Charge",
size = "rel Inten") +
theme(legend.direction = "vertical")
}
} else {
if(interactive){
pep_mass_plot <- ggplot() +
geom_point_interactive(data = rep_mass_dat, aes(x = avg_exp_mass, y = File,
tootlip = glue(
"{Sequence}
Position: {Start}-{End}
Value: {round(avg_exp_mass, 2)},
Replicate: {File}"
)), size = 3) +
geom_vline(xintercept = avg_value, color = "red", linetype = "dashed", linewidth = 1.5) +
annotate("rect",
xmin = avg_value - err_avg, xmax = avg_value + err_avg,
ymin = -Inf, ymax = Inf, fill = "red", alpha=.03) +
labs(y = "",
x = "Measured mass [Da]",
title = paste0("Peptide ", sequence, " in state ", state, " in ", time_t, " min"))
} else {
pep_mass_plot <- ggplot() +
geom_point(data = rep_mass_dat, aes(x = avg_exp_mass, y = File), size = 3) +
geom_vline(xintercept = avg_value, color = "red", linetype = "dashed", linewidth = 1.5) +
annotate("rect",
xmin = avg_value - err_avg, xmax = avg_value + err_avg,
ymin = -Inf, ymax = Inf, fill = "red", alpha=.03) +
labs(y = "",
x = "Measured mass [Da]",
title = paste0("Peptide ", sequence, " in state ", state, " in ", time_t, " min"))
}
}
return(HaDeXify(pep_mass_plot))
}
#' Show peptide mass measurement
#'
#' @description Show the mass measurements
#' from replicates for peptide in specific time point.
#'
#' @param rep_mass_dat data produced by
#' \code{\link{calculate_exp_masses_per_replicate}} function.
#' @param protein chosen protein.
#' @param state biological state for chosen protein.
#' @param sequence sequence of chosen peptide.
#' @param time_t time point of the measurement.
#'
#' @details This function shows the measurements of mass from
#' different replicates for specific peptide in specific state
#' in specific time point of measurement.
#'
#' @return a \code{\link{data.frame}} object.
#'
#' @seealso
#' \code{\link{read_hdx}}
#' \code{\link{calculate_exp_masses_per_replicate}}
#' \code{\link{calculate_exp_masses}}
#' \code{\link{calculate_state_uptake}}
#' \code{\link{calculate_diff_uptake}}
#'
#' @examples
#' rep_mass_dat <- calculate_exp_masses_per_replicate(alpha_dat)
#' show_peptide_mass_measurement(rep_mass_dat)
#'
#' @export show_peptide_mass_measurement
show_peptide_mass_measurement <- function(rep_mass_dat,
protein = rep_mass_dat[["Protein"]][1],
state = rep_mass_dat[["State"]][1],
sequence = rep_mass_dat[["Sequence"]][1],
time_t = unique(rep_mass_dat[["Exposure"]])[3]){
rep_mass_dat <- data.table(rep_mass_dat)
rep_mass_dat <- rep_mass_dat[Protein == protein & State == state & Sequence == sequence & Exposure == time_t]
rep_mass_dat[, avg_exp_mass := round(avg_exp_mass, 4)]
rep_mass_dat <- rep_mass_dat[, .(Protein, Sequence, Start, End, Exposure, State, File, avg_exp_mass)]
setnames(rep_mass_dat, "avg_exp_mass", "Mass")
data.frame(rep_mass_dat)
}
#' Plot peptide charge measurement
#'
#' @description Plot the charge measurements
#' from replicates for peptide in specific time point.
#'
#' @importFrom ggplot2 geom_histogram scale_x_continuous
#'
#' @param dat data as imported by the \code{\link{read_hdx}} function.
#' @param protein chosen protein.
#' @param state biological state for chosen protein.
#' @param sequence sequence of chosen peptide.
#' @param time_t time point of the measurement.
#'
#' @details This function shows the measurements of charge from
#' different replicates for specific peptide in specific state
#' in specific time point of measurement on the plot.
#'
#' @return a [ggplot2::ggplot()] object.
#'
#' @seealso
#' \code{\link{read_hdx}}
#' \code{\link{show_peptide_charge_measurement}}
#'
#' @examples
#' plot_peptide_charge_measurement(alpha_dat)
#'
#' @export plot_peptide_charge_measurement
plot_peptide_charge_measurement <- function(dat,
protein = dat[["Protein"]][1],
state = dat[["State"]][1],
sequence = dat[["Sequence"]][1],
time_t = unique(dat[["Exposure"]])[3]){
dat <- data.table(dat)
tmp_dat <- dat[Protein == protein & State == state & Sequence == sequence & Exposure == time_t]
n_bins <- length(unique(tmp_dat[["z"]]))
min_z <- min(tmp_dat[["z"]])
max_z <- max(tmp_dat[["z"]])
peptide_charge_measurement_plot <- ggplot(tmp_dat, aes(x = z)) +
geom_histogram(aes(fill = File), bins = n_bins) +
scale_x_continuous(breaks = c(min_z:max_z)) +
labs(title = paste0("Peptide ", sequence, " in state ", state, " in ", time_t, " min"))
return(HaDeXify(peptide_charge_measurement_plot))
}
#' Show peptide charge measurement
#'
#' @description Show the charge measurements
#' from replicates for peptide in specific time point.
#'
#' @param dat data as imported by the \code{\link{read_hdx}} function.
#' @param protein chosen protein.
#' @param state biological state for chosen protein.
#' @param sequence sequence of chosen peptide.
#' @param time_t time point of the measurement.
#'
#' @details This function shows the measurements of charge from
#' different replicates for specific peptide in specific state
#' in specific time point of measurement.
#'
#' @return a \code{\link{data.frame}} object.
#'
#' @seealso
#' \code{\link{read_hdx}}
#' \code{\link{plot_peptide_charge_measurement}}
#'
#' @examples
#' show_peptide_charge_measurement(alpha_dat)
#'
#' @export show_peptide_charge_measurement
show_peptide_charge_measurement <- function(dat,
protein = dat[["Protein"]][1],
state = dat[["State"]][1],
sequence = dat[["Sequence"]][1],
time_t = unique(dat[["Exposure"]])[3]){
dat <- data.table(dat)
charge_dat <- dat[Protein == protein & State == state & Sequence == sequence & Exposure == time_t,
.(Protein, Sequence, Start, End, State, Exposure, File, z)]
setorderv(charge_dat, cols = c("z", "File"))
charge_dat
}
#' Create replicates data
#'
#' @description Create replicate data set suitable
#' for replicate histogram, for one or multiple
#' time points of measurement.
#'
#' @param dat data as imported by the \code{\link{read_hdx}} function.
#' @param time_t optional, for only one time point of
#' measurement. If value is NULL, all time point from
#' \code{dat} are preserved.
#' @param protein chosen protein.
#' @param state biological state for chosen protein.
#'
#' @details The function \code{\link{create_replicate_dataset}}
#' creates a dataset with information about how many
#' replicates are for peptides in specific state in
#' time points of measurement.
#'
#' @return a \code{\link{data.frame}} object.
#'
#' @seealso
#' \code{\link{plot_replicate_histogram}}
#' \code{\link{show_replicate_histogram_data}}
#'
#' @examples
#' create_replicate_dataset(alpha_dat)
#'
#' @export create_replicate_dataset
create_replicate_dataset <- function(dat,
time_t = NULL,
protein = unique(dat[["Protein"]])[1],
state = dat[["State"]][1]){
res <- calculate_exp_masses_per_replicate(dat)
## temporarly, for comparability
res <- data.table(res)
##
res <- res[Modification!="", Sequence := paste0(Sequence, "+", Modification)]
res <- if (is.null(time_t)) {
res[Exposure < 99999 & Protein == protein & State == state,
.(Sequence, Exposure, Start, End)]
} else {
res[Exposure == time_t & Protein == protein & State == state,
.(Sequence, Exposure, Start, End)]
}
res <- res[, ID := .GRP, list(Sequence, Start, End)]
setorderv(res, cols = c("Start", "End"))
res <- res[, .(n = .N), by = c("Sequence", "Exposure", "Start", "End", "ID")]
setorderv(res, cols = c("Start", "End", "Exposure"))
## temporarly, for compability
res <- data.frame(res)
##
attr(res, "state") <- state
return(res)
}
#' Plot replicates histogram
#'
#' @description Plot histogram on number of replicates per
#' peptide in one or multiple time point of measurement.
#'
#' @importFrom ggplot2 aes_string
#'
#' @param rep_dat replicate data, created by
#' \code{\link{create_replicate_dataset}} function.
#' @param time_points \code{logical}, indicator if the histogram
#' should show values aggregated for time points of measurements.
#' @inheritParams plot_butterfly
#'
#' @details The function shows three versions of replicate
#' histogram, based on supplied \code{rep_dat} and \code{time_points}.
#' If \code{time_points} is selected, the histogram shows the number
#' of replicates for time points of measurement, to spot
#' if there were troubles with samples for specific time point of
#' measurement. Then, on the X-axis is Exposure (in minutes) and
#' on the Y-axis number of replicates.
#' If \code{time_points} is not selected, on the X-axis there are
#' peptide ID, and on the Y-axis there are numbers of replicates.
#' If \code{rep_dat} contains data from one time point
#' of measurement, the histogram colors reflect the
#' number of replicates to highlight the outliers.
#' If \code{rep_dat} contains multiple time point of
#' measurement, the colors help to distinguish between
#' them.
#'
#' @return a [ggplot2::ggplot()] object.
#'
#' @seealso
#' \code{\link{create_replicate_dataset}}
#' \code{\link{show_replicate_histogram_data}}
#'
#' @examples
#' rep_dat <- create_replicate_dataset(alpha_dat)
#' plot_replicate_histogram(rep_dat)
#'
#' plot_replicate_histogram(rep_dat, time_points = TRUE)
#'
#' rep_dat <- create_replicate_dataset(alpha_dat, time_t = 0.167)
#' plot_replicate_histogram(rep_dat)
#'
#' @export plot_replicate_histogram
plot_replicate_histogram <- function(rep_dat,
time_points = FALSE,
interactive = getOption("hadex_use_interactive_plots")){
state <- attr(rep_dat, "state")
if(time_points){
x <- "Exposure"
fill <- "ID"
legend_position <- "None"
plot_title <- "Number of replicates for time points"
plot_x <- "Exposure [min]"
# TODO: I implemented it here, because those values are calculated internally
# by ggplot -- shouldn't it be moved to data calulation section?
sums <- setNames(sapply(
unique(rep_dat[["Exposure"]]),
function(t) sum(rep_dat[rep_dat[["Exposure"]] == t, "n"])
), unique(rep_dat[["Exposure"]]))
rep_dat[["ctn"]] <- sums[as.character(rep_dat[["Exposure"]])]
tooltip_template <- "Exposure: {Exposure} min,
Peptides: {n}
Total replicates: {ctn}"
chosen_geom_col <- if(interactive){
ggiraph::geom_col_interactive(
aes(x = factor(.data[[x]]), y = n, fill = .data[[fill]],
tooltip = glue(tooltip_template)))
} else {
geom_col(aes(factor(.data[[x]]), y = n, fill = .data[[fill]]))
}
} else {
if (length(unique(rep_dat[["Exposure"]])) == 1) {
x = "ID"
fill <- "n"
legend_position <- "none"
time_t <- unique(rep_dat[["Exposure"]])
plot_title <- paste0("Number of replicates for each peptide in ", state, " state in ", time_t, " min")
plot_x <- "Peptide ID"
tooltip_template <- "{Sequence}
ID: {ID}
Position: {Start}-{End}
Replicates: {n}"
chosen_geom_col <- if (interactive){
ggiraph::geom_col_interactive( aes(tooltip = glue(tooltip_template),
x = .data[[x]], y = n, fill = .data[[fill]]))
} else {
geom_col(aes(x = .data[[x]], y = n, fill = .data[[fill]]))
}
} else {
x <- "ID"
fill <- "Exposure" # factor(Exposure, levels = sort(unique(as.numeric(rep_dat[['Exposure']]))) )"
fct_levels = sort(unique(as.numeric(rep_dat[['Exposure']])))
legend_position <- "bottom"
plot_title <- paste0("Number of replicates for each peptide in ", state, " state")
plot_x <- "Peptide ID"
tooltip_template <- "{Sequence}
ID: {ID}
Position: {Start}-{End}
Exposure: {Exposure} min,
Replicates: {n}"
chosen_geom_col <- if(interactive){
ggiraph::geom_col_interactive( aes(tooltip = glue(tooltip_template),
x = .data[[x]], y = n, fill = factor(.data[[fill]], levels = fct_levels)))
} else {
geom_col( aes(x = .data[[x]], y = n, fill = factor(.data[[fill]], levels = fct_levels)))
}
}
}
replicate_histogram_plot <- ggplot(rep_dat) +
chosen_geom_col +
labs(title = plot_title,
x = plot_x,
y = "Number of replicates",
fill = "Exposure") +
theme(legend.position = legend_position)
return(HaDeXify(replicate_histogram_plot))
}
#' Show replicate data
#'
#' @description Show histogram data on number of replicates per
#' peptide in one or multiple time point of measurement.
#'
#' @param rep_dat replicate data, created by
#' \code{\link{create_replicate_dataset}} function.
#'
#' @details The function shows the information about
#' number of replicates for peptides in one or multiple
#' time point of measurement, depends on supplied data.
#'
#' @return a \code{\link{data.frame}} object.
#'
#' @seealso
#' \code{\link{create_replicate_dataset}}
#' \code{\link{plot_replicate_histogram}}
#'
#' @examples
#' rep_dat <- create_replicate_dataset(alpha_dat)
#' show_replicate_histogram_data(rep_dat)
#'
#' @export show_replicate_histogram_data
show_replicate_histogram_data <- function(rep_dat){
rep_dat <- data.table(rep_dat) ##!!
setorderv(rep_dat, cols = c("Start", "End", "Exposure"))
rep_dat[, .(ID, Sequence, Start, End, Exposure, n)]
rep_dat <- data.frame(rep_dat) ##!!
return(rep_dat)
}
#' Get replicates sd
#'
#' @description Get list of peptides with their standard
#' deviation.
#'
#' @param dat data as imported by the \code{\link{read_hdx}} function.
#' @param protein chosen protein.
#' @param state biological state for chosen protein.
#' @param time_t time point of the measurement.
#'
#' @details Function gets the pepitde list
#' in selected state with their standard deviation
#' of measurement, calculated from the technical
#' replicates. It is used for selection for
#' measurement variability plot.
#'
#' @return a \code{\link{data.frame}} object.
#'
#' @seealso
#' \code{\link{create_replicate_dataset}}
#'
#' @examples
#' get_replicate_list_sd(alpha_dat)
#'
#'
#' @export get_replicate_list_sd
get_replicate_list_sd <- function(dat,
protein = dat[["Protein"]][1],
state = dat[["State"]][1],
time_t = unique(dat[["Exposure"]])[3]){
rep_dat <- calculate_exp_masses_per_replicate(dat)
rep_dat <- data.table(rep_dat)
res <- rep_dat[State == state, .(sd = sd(avg_exp_mass, na.rm = TRUE)), by = c("Sequence", "Start", "End", "Exposure")]
return(data.frame(res))
}
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Defines functions show_peptide_mass_measurement plot_peptide_mass_measurement
Documented in plot_peptide_mass_measurement show_peptide_mass_measurement
#' Plot peptide mass measurement
#'
#' @description Plot the mass measurements
#' from replicates for peptide in specific time point.
#'
#' @importFrom ggplot2 geom_vline annotate
#'
#' @param dat data produced by
#' \code{\link{read_hdx}} function
#' @param protein chosen protein
#' @param state biological state for chosen protein
#' @param sequence sequence of chosen peptide
#' @param show_charge_values \code{logical}, indicator if the data
#' is shown for replicates or for charge values within the
#' replicates
#' @param time_t chosen time point
#' @param interactive \code{logical}, whether plot should have an interactive
#' layer created with with ggiraph, which would add tooltips to the plot in an
#' interactive display (HTML/Markdown documents or shiny app)
#'
#' @details This function shows the measurements of mass from
#' different replicates for specific peptide in specific state
#' in specific time point of measurement on the plot.
#' Moreover, on the plot is shown the average mass from the
#' replicates, used later in calculations. The ribbon next to the
#' dotted average mass indicates the uncertainty.
#'
#' @return a [ggplot2::ggplot()] object.
#'
#' @seealso
#' \code{\link{read_hdx}}
#' \code{\link{calculate_exp_masses_per_replicate}}
#' \code{\link{calculate_exp_masses}}
#' \code{\link{calculate_state_uptake}}
#' \code{\link{calculate_diff_uptake}}
#'
#' @examples
#' plot_peptide_mass_measurement(alpha_dat, sequence = "FGSDDEEESEEAKRLRE")
#' plot_peptide_mass_measurement(alpha_dat, sequence = "FGSDDEEESEEAKRLRE", show_charge_values = FALSE)
#'
#' @export plot_peptide_mass_measurement
plot_peptide_mass_measurement <- function(dat,
protein = dat[["Protein"]][1],
state = dat[["State"]][1],
sequence = dat[["Sequence"]][1],
show_charge_values = TRUE,
time_t = unique(dat[["Exposure"]])[3],
interactive = getOption("hadex_use_interactive_plots")){
rep_mass_dat <- calculate_exp_masses_per_replicate(dat)
## temporarly, for compability
rep_mass_dat <- data.table(rep_mass_dat)
dat <- data.table(dat)
##
rep_mass_dat <- rep_mass_dat[Protein == protein & State == state & Sequence == sequence & Exposure == time_t]
avg_value <- mean(rep_mass_dat[["avg_exp_mass"]])
err_avg <- sd(rep_mass_dat[["avg_exp_mass"]])
if(show_charge_values){
rep_mass_z_dat <- dat[Protein == protein & State == state & Sequence == sequence & Exposure == time_t]
rep_mass_z_dat[, `:=`(exp_mass = Center*z - z*1.00727647,
weighted_Inten = scale(Inten))]
if(interactive){
pep_mass_plot <- ggplot() +
geom_point_interactive(data = rep_mass_z_dat, aes(x = exp_mass, y = File, color = as.factor(z), size = weighted_Inten,
tooltip = glue("{Sequence}
Position: {Start}-{End}
Value: {round(exp_mass, 2)},
Replicate: {File}"
))) +
geom_point_interactive(data = rep_mass_dat, aes(x = avg_exp_mass, y = File,
tooltip = glue("{Sequence}
Position: {Start}-{End}
Value: {round(avg_exp_mass, 2)},
Replicate: {File}")), size = 3) +
geom_vline(xintercept = avg_value, color = "red", linetype = "dashed", linewidth = 1.5) +
annotate("rect",
xmin = avg_value - err_avg, xmax = avg_value + err_avg,
ymin = -Inf, ymax = Inf, fill = "red", alpha=.03) +
labs(y = "",
x = "Measured mass [Da]",
title = paste0("Peptide ", sequence, " in state ", state, " in ", time_t, " min"),
color = "Charge",
size = "rel Inten") +
theme(legend.direction = "vertical")
} else {
pep_mass_plot <- ggplot() +
geom_point(data = rep_mass_z_dat, aes(x = exp_mass, y = File, color = as.factor(z), size = weighted_Inten)) +
geom_point(data = rep_mass_dat, aes(x = avg_exp_mass, y = File), size = 3) +
geom_vline(xintercept = avg_value, color = "red", linetype = "dashed", linewidth = 1.5) +
annotate("rect",
xmin = avg_value - err_avg, xmax = avg_value + err_avg,
ymin = -Inf, ymax = Inf, fill = "red", alpha=.03) +
labs(y = "",
x = "Measured mass [Da]",
title = paste0("Peptide ", sequence, " in state ", state, " in ", time_t, " min"),
color = "Charge",
size = "rel Inten") +
theme(legend.direction = "vertical")
}
} else {
if(interactive){
pep_mass_plot <- ggplot() +
geom_point_interactive(data = rep_mass_dat, aes(x = avg_exp_mass, y = File,
tootlip = glue(
"{Sequence}
Position: {Start}-{End}
Value: {round(avg_exp_mass, 2)},
Replicate: {File}"
)), size = 3) +
geom_vline(xintercept = avg_value, color = "red", linetype = "dashed", linewidth = 1.5) +
annotate("rect",
xmin = avg_value - err_avg, xmax = avg_value + err_avg,
ymin = -Inf, ymax = Inf, fill = "red", alpha=.03) +
labs(y = "",
x = "Measured mass [Da]",
title = paste0("Peptide ", sequence, " in state ", state, " in ", time_t, " min"))
} else {
pep_mass_plot <- ggplot() +
geom_point(data = rep_mass_dat, aes(x = avg_exp_mass, y = File), size = 3) +
geom_vline(xintercept = avg_value, color = "red", linetype = "dashed", linewidth = 1.5) +
annotate("rect",
xmin = avg_value - err_avg, xmax = avg_value + err_avg,
ymin = -Inf, ymax = Inf, fill = "red", alpha=.03) +
labs(y = "",
x = "Measured mass [Da]",
title = paste0("Peptide ", sequence, " in state ", state, " in ", time_t, " min"))
}
}
return(HaDeXify(pep_mass_plot))
}
#' Show peptide mass measurement
#'
#' @description Show the mass measurements
#' from replicates for peptide in specific time point.
#'
#' @param rep_mass_dat data produced by
#' \code{\link{calculate_exp_masses_per_replicate}} function.
#' @param protein chosen protein.
#' @param state biological state for chosen protein.
#' @param sequence sequence of chosen peptide.
#' @param time_t time point of the measurement.
#'
#' @details This function shows the measurements of mass from
#' different replicates for specific peptide in specific state
#' in specific time point of measurement.
#'
#' @return a \code{\link{data.frame}} object.
#'
#' @seealso
#' \code{\link{read_hdx}}
#' \code{\link{calculate_exp_masses_per_replicate}}
#' \code{\link{calculate_exp_masses}}
#' \code{\link{calculate_state_uptake}}
#' \code{\link{calculate_diff_uptake}}
#'
#' @examples
#' rep_mass_dat <- calculate_exp_masses_per_replicate(alpha_dat)
#' show_peptide_mass_measurement(rep_mass_dat)
#'
#' @export show_peptide_mass_measurement
show_peptide_mass_measurement <- function(rep_mass_dat,
protein = rep_mass_dat[["Protein"]][1],
state = rep_mass_dat[["State"]][1],
sequence = rep_mass_dat[["Sequence"]][1],
time_t = unique(rep_mass_dat[["Exposure"]])[3]){
rep_mass_dat <- data.table(rep_mass_dat)
rep_mass_dat <- rep_mass_dat[Protein == protein & State == state & Sequence == sequence & Exposure == time_t]
rep_mass_dat[, avg_exp_mass := round(avg_exp_mass, 4)]
rep_mass_dat <- rep_mass_dat[, .(Protein, Sequence, Start, End, Exposure, State, File, avg_exp_mass)]
setnames(rep_mass_dat, "avg_exp_mass", "Mass")
data.frame(rep_mass_dat)
}
#' Plot peptide charge measurement
#'
#' @description Plot the charge measurements
#' from replicates for peptide in specific time point.
#'
#' @importFrom ggplot2 geom_histogram scale_x_continuous
#'
#' @param dat data as imported by the \code{\link{read_hdx}} function.
#' @param protein chosen protein.
#' @param state biological state for chosen protein.
#' @param sequence sequence of chosen peptide.
#' @param time_t time point of the measurement.
#'
#' @details This function shows the measurements of charge from
#' different replicates for specific peptide in specific state
#' in specific time point of measurement on the plot.
#'
#' @return a [ggplot2::ggplot()] object.
#'
#' @seealso
#' \code{\link{read_hdx}}
#' \code{\link{show_peptide_charge_measurement}}
#'
#' @examples
#' plot_peptide_charge_measurement(alpha_dat)
#'
#' @export plot_peptide_charge_measurement
plot_peptide_charge_measurement <- function(dat,
protein = dat[["Protein"]][1],
state = dat[["State"]][1],
sequence = dat[["Sequence"]][1],
time_t = unique(dat[["Exposure"]])[3]){
dat <- data.table(dat)
tmp_dat <- dat[Protein == protein & State == state & Sequence == sequence & Exposure == time_t]
n_bins <- length(unique(tmp_dat[["z"]]))
min_z <- min(tmp_dat[["z"]])
max_z <- max(tmp_dat[["z"]])
peptide_charge_measurement_plot <- ggplot(tmp_dat, aes(x = z)) +
geom_histogram(aes(fill = File), bins = n_bins) +
scale_x_continuous(breaks = c(min_z:max_z)) +
labs(title = paste0("Peptide ", sequence, " in state ", state, " in ", time_t, " min"))
return(HaDeXify(peptide_charge_measurement_plot))
}
#' Show peptide charge measurement
#'
#' @description Show the charge measurements
#' from replicates for peptide in specific time point.
#'
#' @param dat data as imported by the \code{\link{read_hdx}} function.
#' @param protein chosen protein.
#' @param state biological state for chosen protein.
#' @param sequence sequence of chosen peptide.
#' @param time_t time point of the measurement.
#'
#' @details This function shows the measurements of charge from
#' different replicates for specific peptide in specific state
#' in specific time point of measurement.
#'
#' @return a \code{\link{data.frame}} object.
#'
#' @seealso
#' \code{\link{read_hdx}}
#' \code{\link{plot_peptide_charge_measurement}}
#'
#' @examples
#' show_peptide_charge_measurement(alpha_dat)
#'
#' @export show_peptide_charge_measurement
show_peptide_charge_measurement <- function(dat,
protein = dat[["Protein"]][1],
state = dat[["State"]][1],
sequence = dat[["Sequence"]][1],
time_t = unique(dat[["Exposure"]])[3]){
dat <- data.table(dat)
charge_dat <- dat[Protein == protein & State == state & Sequence == sequence & Exposure == time_t,
.(Protein, Sequence, Start, End, State, Exposure, File, z)]
setorderv(charge_dat, cols = c("z", "File"))
charge_dat
}
#' Create replicates data
#'
#' @description Create replicate data set suitable
#' for replicate histogram, for one or multiple
#' time points of measurement.
#'
#' @param dat data as imported by the \code{\link{read_hdx}} function.
#' @param time_t optional, for only one time point of
#' measurement. If value is NULL, all time point from
#' \code{dat} are preserved.
#' @param protein chosen protein.
#' @param state biological state for chosen protein.
#'
#' @details The function \code{\link{create_replicate_dataset}}
#' creates a dataset with information about how many
#' replicates are for peptides in specific state in
#' time points of measurement.
#'
#' @return a \code{\link{data.frame}} object.
#'
#' @seealso
#' \code{\link{plot_replicate_histogram}}
#' \code{\link{show_replicate_histogram_data}}
#'
#' @examples
#' create_replicate_dataset(alpha_dat)
#'
#' @export create_replicate_dataset
create_replicate_dataset <- function(dat,
time_t = NULL,
protein = unique(dat[["Protein"]])[1],
state = dat[["State"]][1]){
res <- calculate_exp_masses_per_replicate(dat)
## temporarly, for comparability
res <- data.table(res)
##
res <- res[Modification!="", Sequence := paste0(Sequence, "+", Modification)]
res <- if (is.null(time_t)) {
res[Exposure < 99999 & Protein == protein & State == state,
.(Sequence, Exposure, Start, End)]
} else {
res[Exposure == time_t & Protein == protein & State == state,
.(Sequence, Exposure, Start, End)]
}
res <- res[, ID := .GRP, list(Sequence, Start, End)]
setorderv(res, cols = c("Start", "End"))
res <- res[, .(n = .N), by = c("Sequence", "Exposure", "Start", "End", "ID")]
setorderv(res, cols = c("Start", "End", "Exposure"))
## temporarly, for compability
res <- data.frame(res)
##
attr(res, "state") <- state
return(res)
}
#' Plot replicates histogram
#'
#' @description Plot histogram on number of replicates per
#' peptide in one or multiple time point of measurement.
#'
#' @importFrom ggplot2 aes_string
#'
#' @param rep_dat replicate data, created by
#' \code{\link{create_replicate_dataset}} function.
#' @param time_points \code{logical}, indicator if the histogram
#' should show values aggregated for time points of measurements.
#' @inheritParams plot_butterfly
#'
#' @details The function shows three versions of replicate
#' histogram, based on supplied \code{rep_dat} and \code{time_points}.
#' If \code{time_points} is selected, the histogram shows the number
#' of replicates for time points of measurement, to spot
#' if there were troubles with samples for specific time point of
#' measurement. Then, on the X-axis is Exposure (in minutes) and
#' on the Y-axis number of replicates.
#' If \code{time_points} is not selected, on the X-axis there are
#' peptide ID, and on the Y-axis there are numbers of replicates.
#' If \code{rep_dat} contains data from one time point
#' of measurement, the histogram colors reflect the
#' number of replicates to highlight the outliers.
#' If \code{rep_dat} contains multiple time point of
#' measurement, the colors help to distinguish between
#' them.
#'
#' @return a [ggplot2::ggplot()] object.
#'
#' @seealso
#' \code{\link{create_replicate_dataset}}
#' \code{\link{show_replicate_histogram_data}}
#'
#' @examples
#' rep_dat <- create_replicate_dataset(alpha_dat)
#' plot_replicate_histogram(rep_dat)
#'
#' plot_replicate_histogram(rep_dat, time_points = TRUE)
#'
#' rep_dat <- create_replicate_dataset(alpha_dat, time_t = 0.167)
#' plot_replicate_histogram(rep_dat)
#'
#' @export plot_replicate_histogram
plot_replicate_histogram <- function(rep_dat,
time_points = FALSE,
interactive = getOption("hadex_use_interactive_plots")){
state <- attr(rep_dat, "state")
if(time_points){
x <- "Exposure"
fill <- "ID"
legend_position <- "None"
plot_title <- "Number of replicates for time points"
plot_x <- "Exposure [min]"
# TODO: I implemented it here, because those values are calculated internally
# by ggplot -- shouldn't it be moved to data calulation section?
sums <- setNames(sapply(
unique(rep_dat[["Exposure"]]),
function(t) sum(rep_dat[rep_dat[["Exposure"]] == t, "n"])
), unique(rep_dat[["Exposure"]]))
rep_dat[["ctn"]] <- sums[as.character(rep_dat[["Exposure"]])]
tooltip_template <- "Exposure: {Exposure} min,
Peptides: {n}
Total replicates: {ctn}"
chosen_geom_col <- if(interactive){
ggiraph::geom_col_interactive(
aes(x = factor(.data[[x]]), y = n, fill = .data[[fill]],
tooltip = glue(tooltip_template)))
} else {
geom_col(aes(factor(.data[[x]]), y = n, fill = .data[[fill]]))
}
} else {
if (length(unique(rep_dat[["Exposure"]])) == 1) {
x = "ID"
fill <- "n"
legend_position <- "none"
time_t <- unique(rep_dat[["Exposure"]])
plot_title <- paste0("Number of replicates for each peptide in ", state, " state in ", time_t, " min")
plot_x <- "Peptide ID"
tooltip_template <- "{Sequence}
ID: {ID}
Position: {Start}-{End}
Replicates: {n}"
chosen_geom_col <- if (interactive){
ggiraph::geom_col_interactive( aes(tooltip = glue(tooltip_template),
x = .data[[x]], y = n, fill = .data[[fill]]))
} else {
geom_col(aes(x = .data[[x]], y = n, fill = .data[[fill]]))
}
} else {
x <- "ID"
fill <- "Exposure" # factor(Exposure, levels = sort(unique(as.numeric(rep_dat[['Exposure']]))) )"
fct_levels = sort(unique(as.numeric(rep_dat[['Exposure']])))
legend_position <- "bottom"
plot_title <- paste0("Number of replicates for each peptide in ", state, " state")
plot_x <- "Peptide ID"
tooltip_template <- "{Sequence}
ID: {ID}
Position: {Start}-{End}
Exposure: {Exposure} min,
Replicates: {n}"
chosen_geom_col <- if(interactive){
ggiraph::geom_col_interactive( aes(tooltip = glue(tooltip_template),
x = .data[[x]], y = n, fill = factor(.data[[fill]], levels = fct_levels)))
} else {
geom_col( aes(x = .data[[x]], y = n, fill = factor(.data[[fill]], levels = fct_levels)))
}
}
}
replicate_histogram_plot <- ggplot(rep_dat) +
chosen_geom_col +
labs(title = plot_title,
x = plot_x,
y = "Number of replicates",
fill = "Exposure") +
theme(legend.position = legend_position)
return(HaDeXify(replicate_histogram_plot))
}
#' Show replicate data
#'
#' @description Show histogram data on number of replicates per
#' peptide in one or multiple time point of measurement.
#'
#' @param rep_dat replicate data, created by
#' \code{\link{create_replicate_dataset}} function.
#'
#' @details The function shows the information about
#' number of replicates for peptides in one or multiple
#' time point of measurement, depends on supplied data.
#'
#' @return a \code{\link{data.frame}} object.
#'
#' @seealso
#' \code{\link{create_replicate_dataset}}
#' \code{\link{plot_replicate_histogram}}
#'
#' @examples
#' rep_dat <- create_replicate_dataset(alpha_dat)
#' show_replicate_histogram_data(rep_dat)
#'
#' @export show_replicate_histogram_data
show_replicate_histogram_data <- function(rep_dat){
rep_dat <- data.table(rep_dat) ##!!
setorderv(rep_dat, cols = c("Start", "End", "Exposure"))
rep_dat[, .(ID, Sequence, Start, End, Exposure, n)]
rep_dat <- data.frame(rep_dat) ##!!
return(rep_dat)
}
#' Get replicates sd
#'
#' @description Get list of peptides with their standard
#' deviation.
#'
#' @param dat data as imported by the \code{\link{read_hdx}} function.
#' @param protein chosen protein.
#' @param state biological state for chosen protein.
#' @param time_t time point of the measurement.
#'
#' @details Function gets the pepitde list
#' in selected state with their standard deviation
#' of measurement, calculated from the technical
#' replicates. It is used for selection for
#' measurement variability plot.
#'
#' @return a \code{\link{data.frame}} object.
#'
#' @seealso
#' \code{\link{create_replicate_dataset}}
#'
#' @examples
#' get_replicate_list_sd(alpha_dat)
#'
#'
#' @export get_replicate_list_sd
get_replicate_list_sd <- function(dat,
protein = dat[["Protein"]][1],
state = dat[["State"]][1],
time_t = unique(dat[["Exposure"]])[3]){
rep_dat <- calculate_exp_masses_per_replicate(dat)
rep_dat <- data.table(rep_dat)
res <- rep_dat[State == state, .(sd = sd(avg_exp_mass, na.rm = TRUE)), by = c("Sequence", "Start", "End", "Exposure")]
return(data.frame(res))
}
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