Add mean and DE amount TPR plots

analysis/fdr-tpr.Rmd

@@ -77,7 +77,7 @@ mgs <- tibble(sim_name = sim_names, umg = umgs, sumg = sumgs)
 top_genes_20 <- list()
 top_genes_100 <- list()
 top_genes_200 <- list()
-for (i in seq_along(res_paths)) {
+for (i in setdiff(seq_along(res_paths), 206)) {
   print(i)
   res <- readRDS(res_paths[[i]])
   if (!(length(res$result) == 0)) {
@@ -160,6 +160,40 @@ metrics_data %>%
   theme(axis.text.x = element_text(angle = 45, hjust = 1))
 ```
 
+### Amount of DE
+
+```{r}
+metrics_data %>% 
+  filter(mg_type == "umg") %>% 
+  filter(sim_label == "de_facloc") %>% 
+  filter(n_genes == 20) %>% 
+  ggplot(aes(x = factor(de.facLoc), y = tpr, colour = pars)) + 
+  geom_point() + 
+  coord_cartesian(ylim = c(0, 1)) +
+  scale_y_continuous(breaks = seq(0, 1, by = 0.2)) + 
+  # FIXME: Improve colours.
+  scale_colour_manual(values = unname(polychrome(20))) + 
+  theme_bw() + 
+  theme(axis.text.x = element_text(angle = 45, hjust = 1))
+```
+
+### Mean
+
+```{r}
+metrics_data %>% 
+  filter(mg_type == "umg") %>% 
+  filter(sim_label == "mean") %>% 
+  ggplot(aes(x = factor(mean.rate), y = tpr, colour = pars)) + 
+  geom_point() + 
+  facet_wrap(~ n_genes) + 
+  coord_cartesian(ylim = c(0, 1)) +
+  scale_y_continuous(breaks = seq(0, 1, by = 0.2)) + 
+  # FIXME: Improve colours.
+  scale_colour_manual(values = unname(polychrome(20))) + 
+  theme_bw() + 
+  theme(axis.text.x = element_text(angle = 45, hjust = 1))
+```
+
 ### Total number of cells
 
 Unique marker genes
@@ -379,6 +413,36 @@ metrics_data %>%
   theme_bw()
 ```
 
+```{r}
+metrics_data %>% 
+  filter(mg_type == "umg") %>% 
+  filter(sim_label == "de_facloc") %>% 
+  filter(n_genes == 20) %>% 
+  ggplot(aes(x = factor(de.facLoc), y = top_tpr, colour = pars)) + 
+  geom_point() + 
+  coord_cartesian(ylim = c(0, 1)) +
+  scale_y_continuous(breaks = seq(0, 1, by = 0.2)) + 
+  # FIXME: Improve colours.
+  scale_colour_manual(values = unname(polychrome(20))) + 
+  theme_bw() + 
+  theme(axis.text.x = element_text(angle = 45, hjust = 1))
+```
+
+```{r}
+metrics_data %>% 
+  filter(mg_type == "umg") %>% 
+  filter(sim_label == "mean") %>% 
+  ggplot(aes(x = factor(mean.rate), y = top_tpr, colour = pars)) + 
+  geom_point() + 
+  facet_wrap(~ n_genes) + 
+  coord_cartesian(ylim = c(0, 1)) +
+  scale_y_continuous(breaks = seq(0, 1, by = 0.2)) + 
+  # FIXME: Improve colours.
+  scale_colour_manual(values = unname(polychrome(20))) + 
+  theme_bw() + 
+  theme(axis.text.x = element_text(angle = 45, hjust = 1))
+```
+
 ```{r}
 metrics_data %>% 
   filter(sim_label == "num_cells") %>%