now retrieves data for all models and combines into one master table

Author: ymahlich

manuscript/figure4ExVivoResults.Rmd

@@ -66,22 +66,29 @@ print(plot)
 Full model predictions are stored on synapse as parquet files. Individual
 datasets can be downloaded via `getModelPredictionData` in
 `coderdataResultsFunctions.R` (sources during the setup process).
-```{r lgbm data import}
 
-lgbm_all_preds <- getModelPredictionData(dset = "lgbm")
+Here we download data from all models, subset to only MPNST target predictions
+and combine the individual subsets into one master table.
+```{r predictions data import}
 
-```
+tgt = 'mpnst'
 
-```{r subsetting data}
-query <- lgbm_all_preds |>
-  dplyr::filter(target == 'mpnst')
+all_preds <- do.call(
+  rbind,
+  lapply(
+    models,
+    function(mdl) getModelPredictionData(dset = mdl) |>
+      dplyr::filter(target == tgt) |>
+      collect()
+    )
+  )
 
-mpnst_response_data <- query |> collect()
 ```
 
+
 ```{r}
-options(repr.plot.width = 5, repr.plot.height = 15)
-plot <- ggplot(mpnst_response_data, aes(x=auc_true, y=auc_pred)) + geom_point() + geom_smooth(method=lm) + facet_grid(source ~ .)
-ggsave('mpnst_auc_plot.pdf', plot, dpi=300, width=5, height=20)
+plot <- ggplot(all_preds, aes(x=auc_true, y=auc_pred)) + geom_point() + geom_smooth(method=lm) + facet_grid(source ~ model)
+print(plot)
+ggsave('mpnst_auc_plot.pdf', plot, dpi=300, width=20, height=20)
 ```