Merge pull request #274 from ibludau/na_bugfix

Fix normalization from 'per protein' to 'per sample'.
MannLabs · May 17, 2024 · 18ff81b · 18ff81b
2 parents d503c25 + 1bdfbde
commit 18ff81b
Showing 1 changed file with 4 additions and 4 deletions.
diff --git a/alphastats/DataSet_Preprocess.py b/alphastats/DataSet_Preprocess.py
@@ -189,20 +189,20 @@ def _normalization(self, method: str):
 
         if method == "zscore":
             scaler = sklearn.preprocessing.StandardScaler()
-            normalized_array = scaler.fit_transform(self.mat.values)
+            normalized_array = scaler.fit_transform(self.mat.values.transpose()).transpose()
 
         elif method == "quantile":
             qt = sklearn.preprocessing.QuantileTransformer(random_state=0)
-            normalized_array = qt.fit_transform(self.mat.values)
+            normalized_array = qt.fit_transform(self.mat.values.transpose()).transpose()
 
         elif method == "linear":
             normalized_array = self._linear_normalization(self.mat)
 
         elif method == "vst":
             minmax = sklearn.preprocessing.MinMaxScaler()
             scaler = sklearn.preprocessing.PowerTransformer()
-            minmaxed_array = minmax.fit_transform(self.mat.values)
-            normalized_array = scaler.fit_transform(minmaxed_array)
+            minmaxed_array = minmax.fit_transform(self.mat.values.transpose())
+            normalized_array = scaler.fit_transform(minmaxed_array).transpose()
 
         else:
             raise ValueError(