diff --git a/metricsifter/sifter.py b/metricsifter/sifter.py
index 03eeb21..d5ac198 100644
--- a/metricsifter/sifter.py
+++ b/metricsifter/sifter.py
@@ -41,6 +41,26 @@ def filter(x: pd.Series) -> bool:
             return X.loc[:, utils.parallel_apply(X, filter, n_jobs)]
         return X.loc[:, X.apply(filter)]
 
+    def run_upto_cpd(self, data: pd.DataFrame, without_simple_filter: bool = False) -> pd.DataFrame:
+        """ Run up to change point detection"""
+        if without_simple_filter:
+            X = data
+        else:
+            # STEP0: simple filter
+            X = self._filter_no_changes(data, n_jobs=self.n_jobs)
+
+        # STEP1: detect change points
+        _, _, metric_to_cps = detection.detect_multi_changepoints(
+            X,
+            search_method=self.search_method,
+            cost_model=self.cost_model,
+            penalty=self.penalty,
+            penalty_adjust=self.penalty_adjust,
+            n_jobs=self.n_jobs,
+        )
+        remained_metrics = set(metric for metric, cps in metric_to_cps.items() if len(cps) > 0)
+        return X.loc[:, list(remained_metrics)]
+
     def run(self, data: pd.DataFrame, without_simple_filter: bool = False) -> pd.DataFrame:
         if without_simple_filter:
             X = data
@@ -48,7 +68,6 @@ def run(self, data: pd.DataFrame, without_simple_filter: bool = False) -> pd.Dat
             # STEP0: simple filter
             X = self._filter_no_changes(data, n_jobs=self.n_jobs)
 
-        metrics: list[str] = X.columns.tolist()
 
         # STEP1: detect change points
         flatten_change_points, cp_to_metrics, metric_to_cps = detection.detect_multi_changepoints(
@@ -71,14 +90,12 @@ def run(self, data: pd.DataFrame, without_simple_filter: bool = False) -> pd.Dat
         )
 
         # STEP3: select the largest segment
-        remained_metrics = self.select_largest_segment(cluster_label_to_metrics, metrics, metric_to_cps)
+        remained_metrics = self.select_largest_segment(cluster_label_to_metrics, metric_to_cps)
         return X.loc[:, list(remained_metrics)]
 
-
     def select_largest_segment(
         self,
         cluster_label_to_metrics: dict,
-        metrics: list[str],
         metric_to_cps: dict[str, list[int]],
     ) -> set[str]:
         if not cluster_label_to_metrics:
diff --git a/tests/test_sifter.py b/tests/test_sifter.py
index 3b5fa92..7135add 100644
--- a/tests/test_sifter.py
+++ b/tests/test_sifter.py
@@ -19,3 +19,9 @@ def test_sifter_run(synthetic_data_20):
     sifter = Sifter(n_jobs=1)
     siftered_data = sifter.run(data)
     assert siftered_data.shape[1] < data.shape[1], "The number of columns should be reduced."
+
+def test_sifter_run_upto_cpd(synthetic_data_20):
+    data = synthetic_data_20
+    sifter = Sifter(n_jobs=1)
+    siftered_data = sifter.run_upto_cpd(data)
+    assert siftered_data.shape[1] < data.shape[1], "The number of columns should be reduced."