## The following list of commands will generate the plots created in iSEE
## Copy them into a script or an R session containing your SingleCellExperiment.
## All commands below refer to your SingleCellExperiment object as `se`.

se <- sce
colormap <- ExperimentColorMap()
colormap <- synchronizeAssays(colormap, se)
all_contents <- list()

################################################################################
# Defining brushes
################################################################################

all_active <- list()
all_active[['FeatureAssayPlot1']] <- list()

################################################################################
## Feature assay plot 1
################################################################################


plot.data <- data.frame(Y=assay(se, "logcounts")["CD8", ], row.names=colnames(se))
plot.data$X <- assay(se, "logcounts")["CD4", ];

plot.data$ColorBy <- assay(se, "logcounts")["CD16", ];

# Avoid visual biases from default ordering by shuffling the points
set.seed(89869);
plot.data <- plot.data[sample(nrow(plot.data)),,drop=FALSE];

dot.plot <- ggplot() +
  geom_point(aes(x=X, y=Y, color=ColorBy), alpha=1, plot.data, size=1) +
  labs(x="CD4 (logcounts)", y="CD8 (logcounts)", color="CD16\n(logcounts)", title="CD8 vs CD4") +
  coord_cartesian(xlim=range(plot.data$X, na.rm=TRUE),
                  ylim=range(plot.data$Y, na.rm=TRUE), expand=TRUE) +
  scale_color_gradientn(colors=assayColorMap(colormap, "logcounts", discrete=FALSE)(21), na.value='grey50', limits=range(plot.data$ColorBy, na.rm=TRUE)) +
  theme_bw() +
  theme(legend.position='bottom', legend.box='vertical', legend.text=element_text(size=9), legend.title=element_text(size=11),
        axis.text=element_text(size=10), axis.title=element_text(size=12), title=element_text(size=12))

# Saving data for transmission
all_contents[['FeatureAssayPlot1']] <- plot.data