Refactor volcano i

alphastats/plots/VolcanoPlot.py

@@ -13,6 +13,7 @@
 from alphastats.statistics.DifferentialExpressionAnalysis import (
     DifferentialExpressionAnalysis,
 )
+from alphastats.statistics.StatisticUtils import _add_metadata_column
 from alphastats.utils import ignore_warning
 
 # TODO this is repeated and needs to go elsewhere!
@@ -84,15 +85,18 @@ def __init__(
         self.color_list = color_list
 
         if isinstance(group1, list) and isinstance(group2, list):
-            self.metadata, self.column = self._add_metadata_column(
-                metadata, group1, group2
+            self.metadata, self.column = _add_metadata_column(
+                metadata, sample, group1, group2
             )
             self.group1, self.group2 = "group1", "group2"
         else:
             self.metadata, self.column = metadata, column
             self.group1, self.group2 = group1, group2
 
-        self._check_input()
+        if self.column is None:
+            raise ValueError(
+                "Column containing group1 and group2 needs to be specified"
+            )
 
         self._statistics = Statistics(
             mat=self.mat,
@@ -108,35 +112,6 @@ def __init__(
             self._add_hover_data_columns()
             self._plot()
 
-    def _add_metadata_column(
-        self, metadata: pd.DataFrame, group1_list: list, group2_list: list
-    ):
-        # create new column in metadata with defined groups
-
-        sample_names = metadata[self.sample].to_list()
-        misc_samples = list(set(group1_list + group2_list) - set(sample_names))
-        if len(misc_samples) > 0:
-            raise ValueError(
-                f"Sample names: {misc_samples} are not described in Metadata."
-            )
-
-        column = "_comparison_column"
-        conditons = [
-            metadata[self.sample].isin(group1_list),
-            metadata[self.sample].isin(group2_list),
-        ]
-        choices = ["group1", "group2"]
-        metadata[column] = np.select(conditons, choices, default=np.nan)
-
-        return metadata, column
-
-    def _check_input(self):
-        """Check if self.column is set correctly."""
-        if self.column is None:
-            raise ValueError(
-                "Column containing group1 and group2 needs to be specified"
-            )
-
     # TODO revisit this
     def _update(self, updated_attributes):
         """

alphastats/statistics/DifferentialExpressionAnalysis.py

@@ -5,6 +5,7 @@
 import scipy
 
 from alphastats.DataSet_Preprocess import PreprocessingStateKeys
+from alphastats.statistics.StatisticUtils import _add_metadata_column
 
 
 class DifferentialExpressionAnalysis:
@@ -15,34 +16,34 @@ def __init__(
         sample: str,
         index_column: str,
         preprocessing_info: Dict,
-        # TODO move these to perform()?
         group1: Union[str, list],
         group2: Union[str, list],
         column: str = None,
+        # TODO move these to perform()?
         method: str = "ttest",
         perm: int = 10,
         fdr: float = 0.05,
     ):
         self.mat = mat
-        self.metadata = metadata
+
         self.sample = sample
         self.index_column = index_column
         self.preprocessing_info = preprocessing_info
 
-        self.group1 = group1
-        self.group2 = group2
-        self.column = column
         self.method = method
         self.perm = perm
         self.fdr = fdr
 
-    def _check_groups(self):
         if isinstance(self.group1, list) and isinstance(self.group2, list):
-            self.column, self.group1, self.group2 = self._add_metadata_column(
-                self.group1, self.group2
+            self.metadata, self.column = _add_metadata_column(
+                metadata, sample, group1, group2
             )
+            self.group1, self.group2 = "group1", "group2"
+        else:
+            self.metadata, self.column = metadata, column
+            self.group1, self.group2 = group1, group2
 
-        elif self.column is None:
+        if self.column is None:
             raise ValueError(
                 "Column containing group1 and group2 needs to be specified"
             )
@@ -81,29 +82,6 @@ def _prepare_anndata(self):
         )
         return anndata_data
 
-    def _add_metadata_column(self, group1_list: list, group2_list: list):
-        # create new column in metadata with defined groups
-        metadata = self.metadata
-
-        sample_names = metadata[self.sample].to_list()
-
-        misc_samples = list(set(group1_list + group2_list) - set(sample_names))
-        if len(misc_samples) > 0:
-            raise ValueError(
-                f"Sample names: {misc_samples} are not described in Metadata."
-            )
-
-        column = "_comparison_column"
-        conditons = [
-            metadata[self.sample].isin(group1_list),
-            metadata[self.sample].isin(group2_list),
-        ]
-        choices = ["group1", "group2"]
-        metadata[column] = np.select(conditons, choices, default=np.nan)
-        self.metadata = metadata
-
-        return column, "group1", "group2"
-
     def _sam(self) -> pd.DataFrame:  # TODO duplicated? DUP1
         from alphastats.multicova import multicova
 

alphastats/statistics/StatisticUtils.py

@@ -1,29 +1,23 @@
 import numpy as np
+import pandas as pd
 
 
-# TODO: Check if StatisticUtils is used productively anywhere. Otherwise remove it.
-class StatisticUtils:
-    def __init__(self) -> None:
-        pass
+def _add_metadata_column(
+    metadata: pd.DataFrame, sample: str, group1_list: list, group2_list: list
+):
+    # create new column in metadata with defined groups
 
-    def _add_metadata_column(self, group1_list: list, group2_list: list):
-        # create new column in metadata with defined groups
-        metadata = self.metadata
+    sample_names = metadata[sample].to_list()
+    misc_samples = list(set(group1_list + group2_list) - set(sample_names))
+    if len(misc_samples) > 0:
+        raise ValueError(f"Sample names: {misc_samples} are not described in Metadata.")
 
-        sample_names = metadata[self.sample].to_list()
-        misc_samples = list(set(group1_list + group2_list) - set(sample_names))
-        if len(misc_samples) > 0:
-            raise ValueError(
-                f"Sample names: {misc_samples} are not described in Metadata."
-            )
+    column = "_comparison_column"
+    conditons = [
+        metadata[sample].isin(group1_list),
+        metadata[sample].isin(group2_list),
+    ]
+    choices = ["group1", "group2"]
+    metadata[column] = np.select(conditons, choices, default=np.nan)
 
-        column = "_comparison_column"
-        conditons = [
-            metadata[self.sample].isin(group1_list),
-            metadata[self.sample].isin(group2_list),
-        ]
-        choices = ["group1", "group2"]
-        metadata[column] = np.select(conditons, choices, default=np.nan)
-        self.metadata = metadata
-
-        return column, "group1", "group2"
+    return metadata, column