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section renamed and filtering time points fixed #113
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| #' Plot differential uptake curve | ||
| #' | ||
| #' @description | ||
| #' | ||
| #' @param diff_uptake_dat produced by \code{\link{create_diff_uptake_dataset}} function | ||
| #' @param sequence | ||
| #' @param theoretical \code{logical}, determines if plot shows theoretical values. | ||
| #' @param fractional \code{logical}, determines if plot shows fractional values. | ||
| #' @param uncertainty_type type of presenting uncertainty, possible values: | ||
| #' "ribbon", "bars" or "bars + line". | ||
| #' @param log_x \code{logical}, determines if x axis shows logarithmic values. | ||
| #' @param show_houde_interval \code{logical}, determines if houde interval is shown. | ||
| #' @param show_tstud_confidence \code{logical}, determines if t-Student test validity | ||
| #' is shown. | ||
| #' | ||
| #' @details Currently there is no possibility to plot multiple peptides on the plot. | ||
| #' | ||
| #' @return a \code{\link{ggplot2}} object. | ||
| #' | ||
| #' @seealso | ||
| #' \code{\link{read_hdx}} | ||
| #' \code{\link{create_diff_uptake_dataset}} | ||
| #' | ||
| #' @examples | ||
| #' dat <- read_hdx(system.file(package = "HaDeX", "HaDeX/data/KD_180110_CD160_HVEM.csv")) | ||
| #' diff_uptake_dat <- create_diff_uptake_dataset(dat) | ||
| #' plot_differential_uptake_curve(diff_uptake_dat = diff_uptake_dat, sequence = "LCKDRSGDCSPETSLKQL") | ||
| #' | ||
| #' diff_p_uptake_dat <- create_p_diff_uptake_dataset(dat) | ||
| #' plot_differential_uptake_curve(diff_p_uptake_dat = diff_p_uptake_dat, sequence = "LCKDRSGDCSPETSLKQL", show_houde_interval = TRUE) | ||
| #' plot_differential_uptake_curve(diff_p_uptake_dat = diff_p_uptake_dat, sequence = "LCKDRSGDCSPETSLKQL", show_houde_interval = TRUE, show_tstud_confidence = TRUE) | ||
| #' plot_differential_uptake_curve(diff_p_uptake_dat = diff_p_uptake_dat, sequence = "LCKDRSGDCSPETSLKQL", show_tstud_confidence = TRUE) | ||
| #' | ||
| #' @export plot_differential_uptake_curve | ||
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| plot_differential_uptake_curve <- function(diff_uptake_dat = NULL, | ||
| diff_p_uptake_dat = NULL, | ||
| sequence = NULL, | ||
| theoretical = FALSE, | ||
| fractional = FALSE, | ||
| uncertainty_type = "ribbon", | ||
| log_x = TRUE, | ||
| show_houde_interval = FALSE, | ||
| show_tstud_confidence = FALSE){ | ||
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| uncertainty_type <- match.arg(uncertainty_type, c("ribbon", "bars", "bars + line")) | ||
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| if(is.null(sequence)){ sequence <- diff_uptake_dat[["Sequence"]][1] } | ||
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| states <- paste0(attr(diff_uptake_dat, "state_1"), "-", attr(diff_uptake_dat, "state_2")) | ||
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| ## | ||
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| if (show_tstud_confidence) { | ||
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| if(is.null(diff_p_uptake_dat)) { stop("Please, provide the neccessary data.") } else { diff_uptake_dat <- filter(diff_p_uptake_dat, Sequence == sequence) } | ||
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| } else { | ||
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| if(is.null(diff_uptake_dat) & is.null(diff_p_uptake_dat)) { stop("Please, provide the neccessary data.") } else { | ||
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| if(is.null(diff_uptake_dat)) {diff_uptake_dat <- filter(diff_p_uptake_dat, Sequence == sequence) } else { | ||
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| diff_uptake_dat <- filter(diff_uptake_dat, Sequence == sequence) | ||
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| } | ||
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| } | ||
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| } | ||
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| diff_uptake_dat <- filter(diff_uptake_dat, Exposure < 99999) | ||
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| ## | ||
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| if (theoretical){ | ||
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| title <- "Theoretical differential uptake curve" | ||
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| if (fractional){ | ||
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| value <- "diff_theo_frac_deut_uptake" | ||
| err_value <- "err_diff_theo_frac_deut_uptake" | ||
| y_label <- "Fractional differential uptake [%]" | ||
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| } else { | ||
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| value <- "diff_theo_deut_uptake" | ||
| err_value <- "err_diff_theo_deut_uptake" | ||
| y_label <- "Differential uptake [Da]" | ||
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| } | ||
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| } else { | ||
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| title <- "Differential uptake curve" | ||
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| if (fractional){ | ||
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| value <- "diff_frac_deut_uptake" | ||
| err_value <- "err_diff_frac_deut_uptake" | ||
| y_label <- "Fractional differential uptake [%]" | ||
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| } else { | ||
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| value <- "diff_deut_uptake" | ||
| err_value <- "err_diff_deut_uptake" | ||
| y_label <- "Differential uptake [Da]" | ||
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| } | ||
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| } | ||
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| plot_dat <- data.frame(Sequence = diff_uptake_dat[["Sequence"]], | ||
| Start = diff_uptake_dat[["Start"]], | ||
| End = diff_uptake_dat[["End"]], | ||
| Exposure = diff_uptake_dat[["Exposure"]], | ||
| value = diff_uptake_dat[[value]], | ||
| err_value = diff_uptake_dat[[err_value]]) | ||
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| diff_kin_plot <- plot_dat %>% | ||
| ggplot(aes(x = Exposure, y = value, group = Sequence)) + | ||
| geom_point(aes(shape = Sequence, color = states), size = 2) + | ||
| theme(legend.position = "bottom", | ||
| legend.title = element_blank()) + | ||
| labs(x = "Time points [min]", | ||
| y = y_label, | ||
| title = title) | ||
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| if(log_x){ err_width = 0.1 } else { err_width = 5 } | ||
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| if(uncertainty_type == "ribbon"){ | ||
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| diff_kin_plot <- diff_kin_plot + | ||
| geom_ribbon(aes(ymin = value - err_value, ymax = value + err_value, fill = Sequence), alpha = 0.15) + | ||
| geom_line(aes(color = states)) | ||
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| } else if (uncertainty_type == "bars") { | ||
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| diff_kin_plot <- diff_kin_plot + | ||
| geom_errorbar(aes(x = Exposure, ymin = value - err_value, ymax = value + err_value, color = states), | ||
| width = err_width) | ||
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| } else if (uncertainty_type == "bars + line"){ | ||
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| diff_kin_plot <- diff_kin_plot + | ||
| geom_errorbar(aes(x = Exposure, ymin = value - err_value, ymax = value + err_value, color = states), | ||
| width = err_width) + | ||
| geom_line(aes(color = Sequence)) | ||
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| } | ||
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| if(show_houde_interval){ | ||
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| houde_intervals <- diff_uptake_dat %>% | ||
| calculate_confidence_limit_values(confidence_level = attr(diff_uptake_dat, "confidence_level"), | ||
| theoretical = theoretical, | ||
| fractional = fractional) | ||
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| diff_kin_plot <- diff_kin_plot + | ||
| geom_hline(yintercept = houde_intervals[2], linetype = "dashed", color = "red") | ||
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| } | ||
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| if(show_tstud_confidence){ | ||
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| alpha <- -log(1 - attr(diff_uptake_dat, "confidence_level")) | ||
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| diff_uptake_dat <- mutate(diff_uptake_dat, valid = log_p_value >= alpha) %>% | ||
| merge(plot_dat, by = c("Sequence", "Start", "End", "Exposure")) | ||
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| diff_kin_plot <- diff_kin_plot + | ||
| geom_point(data = subset(diff_uptake_dat, !valid), aes(x = Exposure, y = value), shape = 13, size = 2) | ||
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| } | ||
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| if(log_x){ | ||
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| diff_kin_plot <- diff_kin_plot + | ||
| scale_x_log10() | ||
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| } | ||
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| return(HaDeXify(diff_kin_plot)) | ||
|
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| } |
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