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SCE Utils/README.md

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 # SCE-Utils
 Utilities for finding and plotting SCEs in Strand-Seq data.
 
-## Usage from command line:
+## Shiny
+A web app for semi-manual SCE annotation.
+
+## The Scripts `SCE.R` and `plot_all_into_pdf.R`
+A script for finding potential sister chromatid exchanges, and another to plot the results into a pdf.
+
+### Usage from command line:
 ```
 Rscript SCE.R count.table.gz SCEs.txt
 Rscript plot_all_into_pdf.R count.table.gz SCEs.txt output.pdf

SCE Utils/Shiny/README.md

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+# Shiny App for Expert SCE Annotation
+A web application for semi-manual SCE annotation. 
+## Installation
+Download the `server.R`, `ui.R` and `global.R` files and place them in the same folder with each other.
+## Customization
+Edit `server.R` with the details of your data on the lines marked with `'#!#'`. Edit `ui.r` with the names 
+of your users on the lines marked with `'#!#'`. More information is provided in the aforementioned files. **NOTE** You need to 
+have a mosaiCatcher output file, and you need to edit the location of said file into the `server.R`, for this app to work. 
+## Running the App
+**From a terminal:** execute the following, where `~/shinyapp` should be replaced with the path to your application:
+```
+R -e "shiny::runApp('~/shinyapp', launch.browser=TRUE)"
+```
+**From RStudio:** open `server.R` in your RStudio, and click on the _Run App_ text in the top right of the source code pane.

SCE Utils/Shiny/global.R

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+# Shiny app for SCE classification
+# global.R Helper functions
+
+library(shiny)
+library(shinythemes)
+library(htmlwidgets)
+library(data.table)
+library(ggplot2)
+library(shinyjs)
+
+# Pretty printing, courtesy of Sascha Meiers
+format_Mb <- function(x) {
+  paste(scales::comma(x/1e6), "Mb")
+}
+
+# Data initialization, adapted from Sascha Meiers. Some redundance to handle slighly different mosaiCatcher runs.
+initialize_data <- function(e) {
+  e <- e[class != "None",]
+
+  # Order chromosomes.
+  e <- e[, chrom := sub('^chr', '', chrom)][] # get rid of 'chr' if is there
+  e <- e[grepl('^([1-9]|[12][0-9]|X|Y)$', chrom), ] # only looking at standard chromosomes
+  e$chrom <- paste0("chr", e$chrom) # add 'chr' for clarity on plots
+  # Turn the 'chrom' field into a factor, and order it.
+  e <- e[, chrom := factor(chrom, levels=as.character(c(paste0("chr", 1:22),'chrX','chrY')), ordered = T)]
+
+  # A unique identifier for individual cells
+  if (is.null(e$cell_name)) e$cell_name = paste(e$sample, e$cell, sep="_")
+
+  # Find consecutive intervals and number them
+  e <- e[order(cell_name, chrom, start, end),]
+  e$cnsc <- cumsum(e[, .(consecutive = c(1,abs(diff(as.numeric(factor(class)))))), by = .(sample, cell, chrom)]$consecutive)
+
+  return(e)
+}
+
+# Read result files for leaderboard.
+get_results <- function(path, pattern) {
+  files = NULL
+  # List all result files for this dataset.
+  files = list.files(path, pattern = paste0(pattern, ".txt"))
+  results = data.table(cell_name = character(), cell = character(), sample = character(), chrom = character(),
+                       cnsc = character(), end = integer(), user = character(), time = character(), counter = integer())
+  if (!is.null(files) && length(files) > 0) {
+    for (i in files) {
+      a = fread(paste0(path, i), showProgress = F)
+      results = rbind(results, a)
+    }
+  }
+  return(results)
+}
+
+# Main plot with the watson and crick bars. Adapted from Sascha Meiers.
+main_plot <- function(e) {
+  if (the_end) {
+    message <- paste0("\n   Congratulations!\n",
+                 "       You have clicked through all of the chromosomes.\n")
+    plt <- ggplot() +
+      annotate("text", x=10, y=10, label = message) +
+      theme_classic() +
+      theme(panel.spacing = unit(0, "lines"),
+            strip.background = element_rect(fill = NA, colour=NA),
+            rect = element_blank()
+      ) +
+      guides(fill = FALSE)
+
+    return(plt)
+  }
+
+  info_reads_per_bin = stats::median(e$w + e$c)
+  info_y_limit = 2*info_reads_per_bin+1
+
+  chr_end = max(e$end)
+
+  plt <- ggplot(e) + aes(x = (start+end)/2)
+
+  # prepare consecutive rectangles for a better plotting experience
+  consecutive = cumsum(abs(diff(as.numeric(as.factor(e$class)))))
+  consecutive = c(consecutive[1], consecutive)
+  e$consecutive = consecutive
+  f = e[, .(start = min(start), end = max(end), class = class[1]), by = .(consecutive, chrom, sample, cell)][]
+
+  plt <- plt +
+    geom_rect(data = f, aes(xmin = start, xmax=end, ymin=-Inf, ymax=Inf, fill=class),
+              inherit.aes=F, alpha=0.25) +
+    scale_fill_manual(values = c(WW = "sandybrown", CC = "paleturquoise4",
+                                 WC = "yellow", None = NA))
+
+  # Watson/Crick bars
+  plt <- plt +
+    suppressWarnings(geom_bar(aes(y = -w, width=(end-start)),
+                              stat='identity', position = 'identity', fill='sandybrown')) +
+    suppressWarnings(geom_bar(aes(y = c, width=(end-start)),
+                              stat='identity', position = 'identity', fill='paleturquoise4')) +
+
+    ylab("Watson | Crick") + xlab(NULL) +
+    scale_x_continuous(breaks = scales::pretty_breaks(12), labels = format_Mb) +
+    scale_y_continuous(breaks = scales::pretty_breaks(1)) +
+    coord_cartesian(xlim = c(0, chr_end), ylim = c(-info_y_limit, info_y_limit)) +
+    theme_classic() +
+    theme(panel.spacing = unit(0, "lines"),
+          strip.background = element_rect(fill = NA, colour=NA),
+          plot.title = element_text(hjust = 0.5)) +
+    guides(fill = FALSE)
+
+  plt <- plt + facet_grid(sample+cell ~ .) +
+    ggtitle(e$chrom[1], subtitle = NULL)
+
+  return(plt)
+}
+
+# Overlay plot for just the breakpoints
+bkp_plot <- function(e, bkps, highlighted) {
+  if (the_end) {
+    plt <- ggplot() + geom_blank() +
+      theme_classic() +
+      theme(panel.spacing = unit(0, "lines"),
+            strip.background = element_rect(fill = NA, colour=NA),
+            rect = element_blank()
+      ) +
+      guides(fill = FALSE)
+    return(plt)
+  }
+
+  info_reads_per_bin <- round(median(e$w + e$c))
+  info_y_limit <- 2*info_reads_per_bin+1
+
+  chr_end <- max(e$end)
+
+  bkps <- bkps[cnsc %in% e$cnsc]
+
+  plt <- ggplot(bkps) +
+    ylab("Watson | Crick") + xlab(NULL) +
+    scale_x_continuous(breaks = scales::pretty_breaks(12), labels = format_Mb) +
+    scale_y_continuous(breaks = scales::pretty_breaks(1)) +
+    coord_cartesian(xlim = c(0, chr_end), ylim = c(-info_y_limit, info_y_limit)) +
+    theme_classic() +
+    theme(panel.spacing = unit(0, "lines"),
+          strip.background = element_rect(fill = NA, colour=NA),
+          plot.title = element_text(hjust = 0.5),
+          rect = element_blank()
+    ) +
+    guides(fill = FALSE) +
+    facet_grid(sample+cell ~ .) +
+    geom_segment(aes(x=end, y=-info_y_limit, xend=end, yend=info_y_limit),
+                 size=0.4, inherit.aes=F, linetype="dashed", col="dodgerblue") +
+    ggtitle(e$chrom[1], subtitle = NULL)
+
+  if ((!is.null(highlighted)) && (nrow(highlighted)>0)) {
+    plt <- plt + geom_segment(data=highlighted, aes(x=end, y=-info_y_limit, xend=end, yend=info_y_limit), size=0.7, inherit.aes=F, linetype="solid", col="orangered")
+  }
+
+  return(plt)
+}