diff --git a/openms-streamlit-vue-component b/openms-streamlit-vue-component
index 28313bb7..620f2b8e 160000
--- a/openms-streamlit-vue-component
+++ b/openms-streamlit-vue-component
@@ -1 +1 @@
-Subproject commit 28313bb7b777fae10b670f551daacd1e0f4978f6
+Subproject commit 620f2b8e138cbacd8841ba7e2e3d2c9b1df84d2f
diff --git a/src/parse/deconv.py b/src/parse/deconv.py
index 03d9c96d..d7d6bb87 100644
--- a/src/parse/deconv.py
+++ b/src/parse/deconv.py
@@ -26,6 +26,7 @@ def parseDeconv(
         file_manager.store_data(
             dataset_id, f'ms1_{descriptor}_heatmap', heatmap
         )
+
         # Store compressed versions
         for size in reversed(compute_compression_levels(20000, len(heatmap), logger=logger)):
             
diff --git a/src/parse/masstable.py b/src/parse/masstable.py
index f38c8cb2..53e6d9ad 100644
--- a/src/parse/masstable.py
+++ b/src/parse/masstable.py
@@ -193,15 +193,47 @@ def getSpectraTableDF(deconv_df: pd.DataFrame):
 
 
 def getMSSignalDF(anno_df: pd.DataFrame):
-    ints = np.concatenate([anno_df.loc[index, "intarray"] for index in anno_df.index])
-    mzs = np.concatenate([anno_df.loc[index, "mzarray"] for index in anno_df.index])
+    scan_idxs = np.concatenate(
+        [
+            [index]*len(anno_df.loc[index, "intarray"]) 
+            for index in anno_df.index
+        ],
+        dtype=np.int32
+    )
+    mass_idxs = np.concatenate(
+        [
+            list(range(len(anno_df.loc[index, "intarray"]))) 
+            for index in anno_df.index
+        ],
+        dtype=np.int32
+    )
+    ints = np.concatenate(
+        [
+            anno_df.loc[index, "intarray"] 
+            for index in anno_df.index
+        ],
+        dtype=np.float32
+    )
+    mzs = np.concatenate(
+        [
+            anno_df.loc[index, "mzarray"] 
+            for index in anno_df.index
+        ],
+        dtype=np.float32
+    )
     rts = np.concatenate(
         [
             np.full(len(anno_df.loc[index, "mzarray"]), anno_df.loc[index, "RT"])
             for index in anno_df.index
-        ]
+        ],
+        dtype=np.float32
     )
-    ms_df = pd.DataFrame({'mass': mzs, 'rt': rts, 'intensity': ints})
+
+    ms_df = pd.DataFrame({
+        'mass': mzs, 'rt': rts, 'intensity': ints, 
+        'scan_idx': scan_idxs, 'mass_idx': mass_idxs, 
+    })
+
     ms_df.dropna(subset=['intensity'], inplace=True) # remove Nan
     ms_df = ms_df[ms_df['intensity']>0]
     ms_df.sort_values(by='intensity', inplace=True)
diff --git a/src/render/compression.py b/src/render/compression.py
index d49fbdca..51f54b37 100644
--- a/src/render/compression.py
+++ b/src/render/compression.py
@@ -51,6 +51,6 @@ def downsample_heatmap(data, max_datapoints=20000, rt_bins=400, mz_bins=50, logg
         ['mass_bin', 'rt_bin'], group_keys=False, sort=False
     ).head(max_peaks_per_bin).reset_index(drop=True)
 
-    return data.sort_values(by='intensity', ascending=True).loc[
-        :, ['rt', 'mass', 'intensity']
-    ]
+    return data.sort_values(by='intensity', ascending=True).drop(
+        columns=['rank', 'mass_bin', 'rt_bin']
+    )