Merge pull request #11 from Mye-InfoBank/sera/subset_new

select lists for anndata subset dgea

app.py

@@ -38,7 +38,7 @@ def server(input, output, session):
     _model = reactive.value(model_path)
     composition_server("composition", _dataframe)
     export_server("export")
-    dgea_server("dgea", _adata)
+    dgea_server("dgea", _adata, _model)
     tree_server("tree", _tree)
 
 app = App(app_ui, server)

dgea/dgea_scvi.py

@@ -17,13 +17,16 @@ def dgea_ui():
                     )
 
 @module.server
-def dgea_server(input, output, session, _adata: reactive.Value[ad.AnnData]):
+def dgea_server(input, output, session, _adata: reactive.Value[ad.AnnData], _model: reactive.Value[str]):
     _counts = reactive.value(None)
     _uniques = reactive.value([])
+    _sub_uniques = reactive.value([])
 
     _contrast = reactive.value(None)
     _reference = reactive.value(None)
     _alternative = reactive.value(None)
+    _sub_category = reactive.value(None)
+    _chosen_values = reactive.value([])
     _log10_p = reactive.value(0.05)
     _lfc = reactive.value(1)
 
@@ -32,9 +35,9 @@ def dgea_server(input, output, session, _adata: reactive.Value[ad.AnnData]):
     _filtered_genes = reactive.value(None)
     _filtered_counts = reactive.value(None)
 
-    run_dgea_server("run_dgea", _adata, _result, _counts, _reference, _alternative, _uniques, _contrast)
+    run_dgea_server("run_dgea", _adata, _result, _counts, _reference, _alternative, _model, _uniques, _contrast, _sub_category, _chosen_values, _sub_uniques)
     filter_dgea_server("filter_dgea", _adata, _counts, _uniques,
                        _result, _filtered_result, _filtered_genes,
-                       _filtered_counts, _reference, _alternative, _contrast, _log10_p, _lfc)
+                       _filtered_counts, _reference, _alternative, _contrast, _sub_category, _sub_uniques, _chosen_values, _model, _log10_p, _lfc)
     plot_dgea_server("plot_dgea", _filtered_counts, _contrast, _reference, _alternative,
                      _result, _log10_p, _lfc)

dgea/filter_dgea_scvi.py

@@ -6,6 +6,7 @@
 @module.ui
 def filter_dgea_ui():
     return ui.div(
+        ui.output_ui("select_values"),
         ui.output_ui("select_reference"),
         ui.output_ui("select_alternative"),
         ui.input_slider("log10_pscore", "Ropability in Reference (significance threshold)", min=0, max=20, step=0.01, value=3),
@@ -17,10 +18,17 @@ def filter_dgea_ui():
 def filter_dgea_server(input, output, session, 
                        _adata, _counts, _uniques,
                        _result, _filtered_result, _filtered_genes, _filtered_counts,
-                       _reference, _alternative, _contrast,
+                       _reference, _alternative, _contrast, _sub_category, _sub_uniques, _chosen_values, _model,
                        _log10_p, _lfc
                        ):
 
+    @output
+    @render.ui
+    def select_values():
+        sub_uniques = _sub_uniques.get()
+
+        return ui.input_select("value", "Choose values:", choices=sub_uniques, selectize=True, multiple=True, selected=sub_uniques)
+
     @output
     @render.ui
     def select_reference():
@@ -46,26 +54,12 @@ def select_alternative():
 
     @reactive.effect
     def update_filters():
+        _chosen_values.set(input["value"].get())
         _reference.set(input["reference"].get())
         _alternative.set(input["alternative"].get())
         _log10_p.set(input["log10_pscore"].get())
         _lfc.set(input["lfc"].get())
 
-    @reactive.effect
-    def update_result():
-        adata = _adata.get()
-        reference = _reference.get()
-        alternative = _alternative.get()
-        contrast = _contrast.get()
-
-        if None in (reference, alternative, contrast):
-            return
-
-        res_df = scanvi_dgea(adata, contrast, reference, alternative)
-        res_counts = get_normalized_counts(adata)
-        _result.set(res_df)
-        _counts.set(res_counts)
-
     @reactive.effect
     def filter_result():
         result = _result.get()

dgea/plot_dgea_scvi.py

@@ -38,9 +38,6 @@ def plot_dgea_server(input, output, session,
     @render.plot
     def plot_heatmap():
         counts_df = _filtered_counts.get()
-        contrast = _contrast.get()
-        reference = _reference.get()
-        alternative = _alternative.get()
 
         if counts_df is None:
             return None

dgea/run_dgea_scvi.py

@@ -8,7 +8,8 @@
 @module.ui
 def run_dgea_ui():
     return ui.div(ui.output_ui("contrast_selector"),
-              ui.input_task_button("run", "Run analysis"))
+                ui.output_ui("subset_selector"),
+                ui.input_task_button("run", "Run analysis"))
 
 @module.server
 def run_dgea_server(input, output, session,
@@ -19,7 +20,10 @@ def run_dgea_server(input, output, session,
                     _alternative: reactive.Value[str],
                     _model: reactive.Value[str],
                     _uniques: reactive.Value[list],
-                    _contrast: reactive.Value[str]):
+                    _contrast: reactive.Value[str],
+                    _sub_category: reactive.Value[str],
+                    _chosen_values: reactive.Value[list],
+                    _sub_uniques: reactive.Value[list]):
     _category_columns = reactive.value([])
     _numeric_columns = reactive.value([])
 
@@ -38,10 +42,22 @@ def contrast_selector():
 
         return ui.input_select("contrast", "Contrast", choices=columns, selected=columns[0])
 
+    @output
+    @render.ui
+    def subset_selector():
+        columns = _category_columns.get()
+
+        return ui.input_select("sub_category", "Category to subset", choices=columns, selected=columns[0])
+
     @reactive.effect
     def update_contrast():
         contrast = input["contrast"].get()
         _contrast.set(contrast)
+
+    @reactive.effect    
+    def update_subset():
+        sub_category = input["sub_category"].get()
+        _sub_category.set(sub_category)
 
     @reactive.effect
     @reactive.event(input["run"])
@@ -51,7 +67,10 @@ def handle_run():
         referece = _reference.get()
         alternative = _alternative.get()
         model = _model.get()
-        run_scanvi(adata, contrast, referece, alternative, model)
+        sub_category = _sub_category.get()
+        chosen_values = _chosen_values.get()
+        adata_subset = adata[adata.obs[sub_category].isin(chosen_values)].copy()
+        run_scanvi(adata_subset, contrast, referece, alternative, model)
 
     @reactive.effect
     def update_scanvi_result():
@@ -75,3 +94,12 @@ def update_uniques():
             return
         uniques = adata.obs[contrast].unique().tolist()
         _uniques.set(uniques)
+
+    @reactive.effect
+    def update_sub_uniques():
+        adata = _adata.get()
+        sub_category = _sub_category.get()
+        if adata is None or sub_category is None:
+            return
+        sub_uniques = adata.obs[sub_category].unique().tolist()
+        _sub_uniques.set(sub_uniques)

docker-compose.yml

@@ -5,4 +5,4 @@ services:
       dockerfile: Dockerfile
     ports:
       - 8080:8080
-    image: bigdatainbiomedicine/simba-downstream:0.3.0
+    image: bigdatainbiomedicine/simba-downstream:0.3.1