Refactor analysis v

alphastats/gui/pages/04_Analysis.py

@@ -6,9 +6,6 @@
     display_plot,
     do_analysis,
 )
-from alphastats.gui.utils.options import (
-    get_statistic_options,
-)
 from alphastats.gui.utils.ui_helper import (
     StateKeys,
     convert_df,
@@ -35,6 +32,8 @@
     """
 st.markdown(styl, unsafe_allow_html=True)
 
+# TODO put everything in the session state for a given parameter set?
+# or is caching functionality the way to go here?
 
 if StateKeys.DATASET not in st.session_state:
     st.info("Import Data first")
@@ -55,12 +54,7 @@
         + ["------- plots -------"]
         + plotting_options
         + ["------- statistics -------"]
-        + statistic_options
-        + [
-            k
-            for k in get_statistic_options(st.session_state)
-            if k not in statistic_options
-        ],
+        + statistic_options,
     )
 
     if method in plotting_options:
@@ -69,14 +63,10 @@
         )
         show_plot = analysis_result is not None
 
-    elif (
-        method
-        in list((options := get_statistic_options(st.session_state)).keys())
-        + statistic_options
-    ):
+    elif method in statistic_options:
         analysis_result, *_ = do_analysis(
             method,
-            options_dict=options,
+            options_dict=None,
         )
         show_df = analysis_result is not None
 

alphastats/gui/utils/analysis.py

@@ -40,6 +40,8 @@ class PlottingOptions(metaclass=ConstantsClass):
 class StatisticOptions(metaclass=ConstantsClass):
     DIFFERENTIAL_EXPRESSION = "Differential Expression Analysis"
     TUKEY_TEST = "Tukey-Test"
+    ANOVA = "ANOVA"
+    ANCOVA = "ANCOVA"
 
 
 class Analysis(ABC):
@@ -384,3 +386,67 @@ def _do_analysis(self):
             group=self._parameters["group"],
         )
         return tukey_test_analysis, None, self._parameters
+
+
+class AnovaAnalysis(GroupCompareAnalysis):
+    """Widget for ANOVA analysis."""
+
+    def show_widget(self):
+        """Show the widget and gather parameters."""
+
+        column = st.selectbox(
+            "A variable from the metadata to calculate ANOVA",
+            options=self._dataset.metadata.columns.to_list(),
+        )
+        protein_ids = st.selectbox(
+            "All ProteinIDs/or specific ProteinID to perform ANOVA",
+            options=["all"] + self._dataset.mat.columns.to_list(),
+        )
+
+        tukey = st.checkbox("Follow-up Tukey")
+
+        self._parameters.update(
+            {"column": column, "protein_ids": protein_ids, "tukey": tukey}
+        )
+
+    def _do_analysis(self):
+        """Perform Anova analysis."""
+        anova_analysis = self._dataset.anova(
+            column=self._parameters["column"],
+            protein_ids=self._parameters["protein_ids"],
+            tukey=self._parameters["tukey"],
+        )
+        return anova_analysis, None, self._parameters
+
+
+class AncovaAnalysis(Analysis):
+    """Widget for Ancova analysis."""
+
+    def show_widget(self):
+        """Show the widget and gather parameters."""
+
+        protein_id = st.selectbox(
+            "ProteinID/ProteinGroup",
+            options=self._dataset.mat.columns.to_list(),
+        )
+        covar = st.selectbox(
+            "Name(s) of column(s) in metadata with the covariate.",
+            options=self._dataset.metadata.columns.to_list(),
+        )  # TODO: why plural if only one can be selected?
+        between = st.selectbox(
+            "Name of the column in the metadata with the between factor.",
+            options=self._dataset.metadata.columns.to_list(),
+        )
+
+        self._parameters.update(
+            {"protein_id": protein_id, "covar": covar, "between": between}
+        )
+
+    def _do_analysis(self):
+        """Perform ANCOVA analysis."""
+        ancova_analysis = self._dataset.ancova(
+            protein_id=self._parameters["protein_id"],
+            covar=self._parameters["covar"],
+            between=self._parameters["between"],
+        )
+        return ancova_analysis, None, self._parameters

alphastats/gui/utils/analysis_helper.py

@@ -5,6 +5,8 @@
 import streamlit as st
 
 from alphastats.gui.utils.analysis import (
+    AncovaAnalysis,
+    AnovaAnalysis,
     ClustermapAnalysis,
     DifferentialExpressionAnalysis,
     IntensityPlot,
@@ -152,6 +154,8 @@ def do_analysis(
         # "Dendrogram": dataet.plot_dendrogram},  # TODO this was commented out in the original code?
         StatisticOptions.DIFFERENTIAL_EXPRESSION: DifferentialExpressionAnalysis,
         StatisticOptions.TUKEY_TEST: TukeyTestAnalysis,
+        StatisticOptions.ANOVA: AnovaAnalysis,
+        StatisticOptions.ANCOVA: AncovaAnalysis,
     }
 
     if (analysis_class := options.get(method)) is not None:

alphastats/gui/utils/options.py

@@ -1,52 +1,11 @@
 from alphastats import SpectronautLoader
-from alphastats.gui.utils.ui_helper import StateKeys
 from alphastats.loader.AlphaPeptLoader import AlphaPeptLoader
 from alphastats.loader.DIANNLoader import DIANNLoader
 from alphastats.loader.FragPipeLoader import FragPipeLoader
 from alphastats.loader.GenericLoader import GenericLoader
 from alphastats.loader.MaxQuantLoader import MaxQuantLoader
 from alphastats.loader.mzTabLoader import mzTabLoader
 
-
-def get_statistic_options(state):
-    dataset = state[StateKeys.DATASET]
-    metadata_options = dataset.metadata.columns.to_list()
-    statistic_options = {
-        "ANOVA": {
-            "settings": {
-                "column": {
-                    "options": metadata_options,
-                    "label": "A variable from the metadata to calculate ANOVA",
-                },
-                "protein_ids": {
-                    "options": ["all"] + dataset.mat.columns.to_list(),
-                    "label": "All ProteinIDs/or specific ProteinID to perform ANOVA",
-                },
-                "tukey": {"label": "Follow-up Tukey"},
-            },
-            "function": dataset.anova,
-        },
-        "ANCOVA": {
-            "settings": {
-                "protein_id": {
-                    "options": [None] + dataset.mat.columns.to_list(),
-                    "label": "Color according to",
-                },
-                "covar": {
-                    "options": metadata_options,
-                    "label": "Name(s) of column(s) in metadata with the covariate.",
-                },
-                "between": {
-                    "options": metadata_options,
-                    "label": "Name of the column in the metadata with the between factor.",
-                },
-            },
-            "function": dataset.ancova,
-        },
-    }
-    return statistic_options
-
-
 SOFTWARE_OPTIONS = {
     "MaxQuant": {
         "import_file": "Please upload proteinGroups.txt",