diff --git a/public/R/queueJobReport.R b/public/R/queueJobReport.R
new file mode 100644
index 000000000..18d33054e
--- /dev/null
+++ b/public/R/queueJobReport.R
@@ -0,0 +1,154 @@
+library(gsalib)
+require("ggplot2")
+require("gplots")
+
+#
+# Standard command line switch.  Can we loaded interactively for development
+# or executed with RScript
+#
+args = commandArgs(TRUE)
+onCMDLine = ! is.na(args[1])
+if ( onCMDLine ) {
+  inputFileName = args[1]
+  outputPDF = args[2]
+} else {
+  inputFileName = "~/Desktop/broadLocal/GATK/unstable/report.txt"
+  outputPDF = NA
+}
+
+RUNTIME_UNITS = "(sec)"
+ORIGINAL_UNITS_TO_SECONDS = 1/1000
+
+# 
+# Helper function to aggregate all of the jobs in the report across all tables
+#
+allJobsFromReport <- function(report) {
+  names <- c("jobName", "startTime", "analysisName", "doneTime", "exechosts")
+  sub <- lapply(report, function(table) table[,names])
+  do.call("rbind", sub)
+}
+
+#
+# Creates segmentation plots of time (x) vs. job (y) with segments for the duration of the job
+#
+plotJobsGantt <- function(gatkReport, sortOverall) {
+  allJobs = allJobsFromReport(gatkReport)
+  if ( sortOverall ) {
+    title = "All jobs, by analysis, by start time"
+    allJobs = allJobs[order(allJobs$analysisName, allJobs$startTime, decreasing=T), ]
+  } else {
+    title = "All jobs, sorted by start time"
+    allJobs = allJobs[order(allJobs$startTime, decreasing=T), ]
+  }
+  allJobs$index = 1:nrow(allJobs)
+  minTime = min(allJobs$startTime)
+  allJobs$relStartTime = allJobs$startTime - minTime
+  allJobs$relDoneTime = allJobs$doneTime - minTime
+  allJobs$ganttName = paste(allJobs$jobName, "@", allJobs$exechosts)
+  maxRelTime = max(allJobs$relDoneTime)
+  p <- ggplot(data=allJobs, aes(x=relStartTime, y=index, color=analysisName))
+  p <- p + geom_segment(aes(xend=relDoneTime, yend=index), size=2, arrow=arrow(length = unit(0.1, "cm")))
+  p <- p + geom_text(aes(x=relDoneTime, label=ganttName, hjust=-0.2), size=2)
+  p <- p + xlim(0, maxRelTime * 1.1)
+  p <- p + xlab(paste("Start time (relative to first job)", RUNTIME_UNITS))
+  p <- p + ylab("Job")
+  p <- p + opts(title=title)
+  print(p)
+}
+
+#
+# Plots scheduling efficiency at job events
+#
+plotProgressByTime <- function(gatkReport) {
+  allJobs = allJobsFromReport(gatkReport)
+  nJobs = dim(allJobs)[1]
+  allJobs = allJobs[order(allJobs$startTime, decreasing=F),]
+  allJobs$index = 1:nrow(allJobs)
+
+  minTime = min(allJobs$startTime)
+  allJobs$relStartTime = allJobs$startTime - minTime
+  allJobs$relDoneTime = allJobs$doneTime - minTime
+
+  times = sort(c(allJobs$relStartTime, allJobs$relDoneTime))
+
+  countJobs <- function(p) {
+    s = allJobs$relStartTime
+    e = allJobs$relDoneTime
+    x = c() # I wish I knew how to make this work with apply
+    for ( time in times )
+      x = c(x, sum(p(s, e, time)))
+    x
+  }
+
+  pending = countJobs(function(s, e, t) s > t)
+  done = countJobs(function(s, e, t) e < t)
+  running = nJobs - pending - done
+
+  d = data.frame(times=times, pending=pending, running=running, done=done)
+  
+  p <- ggplot(data=melt(d, id.vars=c("times")), aes(x=times, y=value, color=variable))
+  p <- p + facet_grid(variable ~ ., scales="free")
+  p <- p + geom_line(size=2)
+  p <- p + xlab(paste("Time since start of first job", RUNTIME_UNITS))
+  p <- p + opts(title = "Job scheduling")
+  print(p)
+}
+
+# 
+# Creates tables for each job in this group
+#
+standardColumns = c("jobName", "startTime", "formattedStartTime", "analysisName", "intermediate", "exechosts", "formattedDoneTime", "doneTime", "runtime")
+plotGroup <- function(groupTable) {
+  name = unique(groupTable$analysisName)[1]
+  groupAnnotations = setdiff(names(groupTable), standardColumns)  
+  sub = groupTable[,c("jobName", groupAnnotations, "runtime")]
+  sub = sub[order(sub$iteration, sub$jobName, decreasing=F), ]
+  
+  # create a table showing each job and all annotations
+  textplot(sub, show.rownames=F)
+  title(paste("Job summary for", name, "full itemization"), cex=3)
+
+  # create the table for each combination of values in the group, listing iterations in the columns
+  sum = cast(melt(sub, id.vars=groupAnnotations, measure.vars=c("runtime")), ... ~ iteration, fun.aggregate=mean)
+  textplot(as.data.frame(sum), show.rownames=F)
+  title(paste("Job summary for", name, "itemizing each iteration"), cex=3)
+
+  # as above, but averaging over all iterations
+  groupAnnotationsNoIteration = setdiff(groupAnnotations, "iteration")
+  sum = cast(melt(sub, id.vars=groupAnnotationsNoIteration, measure.vars=c("runtime")), ... ~ ., fun.aggregate=c(mean, sd))
+  textplot(as.data.frame(sum), show.rownames=F)
+  title(paste("Job summary for", name, "averaging over all iterations"), cex=3)
+}
+    
+# print out some useful basic information
+print("Report")
+print(paste("Project          :", inputFileName))
+
+convertUnits <- function(gatkReportData) {
+  convertGroup <- function(g) {
+    g$runtime = g$runtime * ORIGINAL_UNITS_TO_SECONDS
+    g
+  }
+  lapply(gatkReportData, convertGroup)
+}
+
+  
+# read the table
+gatkReportData <- gsa.read.gatkreport(inputFileName)
+gatkReportData <- convertUnits(gatkReportData)
+#print(summary(gatkReportData))
+
+if ( ! is.na(outputPDF) ) {
+  pdf(outputPDF, height=8.5, width=11)
+} 
+
+plotJobsGantt(gatkReportData, T)
+plotJobsGantt(gatkReportData, F)
+plotProgressByTime(gatkReportData)
+for ( group in gatkReportData ) {
+  plotGroup(group)
+}
+  
+if ( ! is.na(outputPDF) ) {
+  dev.off()
+}