diff --git a/spectrum_io/search_result/sage.py b/spectrum_io/search_result/sage.py
index ccec3a8..920a33a 100644
--- a/spectrum_io/search_result/sage.py
+++ b/spectrum_io/search_result/sage.py
@@ -26,15 +26,7 @@ def read_result(path: Union[str, Path], tmt_labeled: str = "") -> pd.DataFrame:
         logger.info("Reading msms.tsv file")
         df = pd.read_csv(
             path,
-            usecols=[
-                "filename",
-                "scannr",
-                "peptide",
-                "charge",
-                "hyperscore",
-                "calcmass",
-                "proteins"
-            ],
+            usecols=["filename", "scannr", "peptide", "charge", "hyperscore", "calcmass", "proteins"],
             sep="\t",
         )
         logger.info("Finished reading msms.tsv file")
@@ -65,9 +57,9 @@ def update_columns_for_prosit(df: pd.DataFrame, tmt_labeled: str) -> pd.DataFram
         )
 
         # removing .mzML
-        df['RAW_FILE'] = df['RAW_FILE'].str.replace(".mzML","",regex=True)
-        # extracting only the scan number 
-        df['SCAN_NUMBER'] = df['SCAN_NUMBER'].str.split('=').str[3:].str.join('=')
+        df["RAW_FILE"] = df["RAW_FILE"].str.replace(".mzML", "", regex=True)
+        # extracting only the scan number
+        df["SCAN_NUMBER"] = [int(x.rsplit("=", 1)[-1]) for x in df["SCAN_NUMBER"]]
         # creating a column of decoys and targets
         df["REVERSE"] = df["PROTEINS"].str.startswith("rev_")
         # removing modification to create the unmodified sequences
diff --git a/tests/unit_tests/test_sage.py b/tests/unit_tests/test_sage.py
index 33085e1..d136356 100644
--- a/tests/unit_tests/test_sage.py
+++ b/tests/unit_tests/test_sage.py
@@ -2,6 +2,7 @@
 from pathlib import Path
 
 import pandas as pd
+
 from spectrum_io.search_result import Sage
 
 
@@ -14,8 +15,6 @@ def test_read_sage(self):
         expected_sage_internal_path = Path(__file__).parent / "data" / "sage_output_internal.csv"
 
         internal_search_results_df = Sage.read_result(sage_output_path)
+        expected_df = pd.read_csv(expected_sage_internal_path, index_col=0)
 
-        # execute only once, then remove and test again
-        internal_search_results_df.to_csv(expected_sage_internal_path)
-
-        self.assertEqual(internal_search_results_df, pd.read_csv(expected_sage_internal_path))
+        pd.testing.assert_frame_equal(internal_search_results_df, expected_df)