Update network plotting code

Author: William Ryan

data.qmd

@@ -256,7 +256,7 @@ get_chea3_enrichment <- function(genes, query_name = "myQuery", url = "https://m
 #Predict transcription factors involved in all the data so far
 chea3_results <- get_chea3_enrichment(data %>% map(pull, name) %>% unlist) %>%
   percentile_rank(`TF`, `Rank`, desc = TRUE) %>%
-  top_hits(prec_cutoff = -0.1, omic_type = "TF")
+  top_hits(prec_cutoff = .9, omic_type = "TF") #Currently, select the top 10%
 
 # CHEA3 always returns human symbols, lets convert back.
 if(params$species != "human") {
@@ -294,15 +294,15 @@ ppi <- bind_rows(string_ppi, phuego_ppi) %>%
     summarise(cost = mean(cost)) %>%
     ungroup()
 
-kinograte_res <- quiet(kinograte(combined_df# %>% slice_sample(n=1000)
+kinograte_res <- quiet(kinograte(combined_df %>% slice_sample(n=250)
                                  , ppi_network = ppi, cluster = F, seed = 123, mu=1e-4))
 ```
 
 ```{r}
 #| label: "data_visualizations"
 make_table(combined_df)
 
-score_plot <- function(df, prec_cutoff = 0.8, title = "Prize Plot", subtitle = "", interactive = T) {
+score_plot <- function(df, title = "Prize Plot", subtitle = "", interactive = T) {
   
   df %>% 
     dplyr::mutate_if(is.numeric, round, 3) -> df
@@ -314,7 +314,6 @@ score_plot <- function(df, prec_cutoff = 0.8, title = "Prize Plot", subtitle = "
       echarts4r::e_visual_map(score) %>% 
       echarts4r::e_x_axis(axisLabel =  list(show  = F)) %>% 
       echarts4r::e_y_axis(name = "Normalized Prize", nameLocation = "center", nameGap = 40, nameTextStyle =  list()) %>% 
-      #echarts4r::e_mark_line(data = list(yAxis = prec_cutoff), title = "Score Cutoff", symbolSize = F, silent = T) %>% 
       echarts4r::e_tooltip(trigger = "axis") %>% 
       echarts4r::e_title(title, subtext = subtitle)
   }

networks.qmd

@@ -5,7 +5,7 @@ date: last-modified
 date-format: "[Last Updated on] MMMM DD, YYYY"
 ---
 
-These are your pathways.
+These are your networks.
 
 ```{r}
 #| label: "networks_common"
@@ -31,15 +31,14 @@ generate_subnetwork <- function(kinograte_res, genes) {
          Kinase = as.numeric(str_detect(type.y, "Kinase")),
          Hidden = as.numeric(str_detect(type.y, "Hidden")),
          Protein = as.numeric(str_detect(type.y, "Protein")),
-         Special = sample(c(TRUE, FALSE), nrow(.), replace = TRUE))
+         Peptide = as.numeric(str_detect(type.y, "Peptide")),
+         TF = as.numeric(str_detect(type.y, "TF")))
 
   plot = plot_data %>%
     ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
     geom_edges(color = "grey50", curvature = 0.05) +
-    #geom_nodes(aes(color=Special), size=11)+
-    #geom_nodes(size=9, color = "white")+
-    geom_scatterpie(data = plot_data %>% distinct(vertex.names, .keep_all = TRUE), cols = c("RNA", "Protein", "Kinase", "Hidden"), pie_scale = .5) + 
-    geom_nodetext_repel(aes(label = vertex.names), fontface = "bold", size = 11 / ggplot2:::.pt, box.padding = unit(.35, "lines")) +
+    geom_scatterpie(data = plot_data %>% distinct(vertex.names, .keep_all = TRUE), cols = c("RNA", "Kinase", "Hidden", "Protein", "Peptide", "TF"), pie_scale = .5) + 
+    geom_nodetext_repel(aes(label = vertex.names), family = "Arial Narrow", fontface = "bold.italic", size = 9 / ggplot2:::.pt, box.padding = unit(.25, "lines")) +
     coord_equal() +
     theme_blank() +
     theme(legend.position = "none")
@@ -50,7 +49,7 @@ generate_subnetwork <- function(kinograte_res, genes) {
 ```
 
 ```{r}
-genes_input <- gsea_pathways[831, ]$leadingEdge %>% unlist()
+genes_input <- names(combined) %>% sample(100)
 
 plot <- generate_subnetwork(kinograte_res, genes_input)