diff --git a/MARBLE/preprocessing.py b/MARBLE/preprocessing.py
index 0d072677..e0d5af3d 100644
--- a/MARBLE/preprocessing.py
+++ b/MARBLE/preprocessing.py
@@ -21,6 +21,7 @@ def construct_dataset(
     number_of_resamples=1,
     var_explained=0.9,
     local_gauges=False,
+    start_idx=None,
 ):
     """Construct PyG dataset from node positions and features.
 
@@ -40,6 +41,7 @@ def construct_dataset(
         var_explained: fraction of variance explained by the local gauges
         local_gauges: is True, it will try to compute local gauges if it can (signal dim is > 2,
             embedding dimension is > 2 or dim embedding is not dim of manifold)
+        start_idx: Specify for reproducibility in the furthest point sampling. The default is None, which means a random starting vertex.
     """
 
     anchor = [torch.tensor(p).float() for p in utils.to_list(anchor)]
@@ -63,7 +65,8 @@ def construct_dataset(
     for i, (a, v, l, m) in enumerate(zip(anchor, vector, label, mask)):
         for _ in range(number_of_resamples):
             # even sampling of points
-            start_idx = torch.randint(low=0, high=len(a), size=(1,))
+            start_idx is None:
+                start_idx = torch.randint(low=0, high=len(a), size=(1,))
             sample_ind, _ = g.furthest_point_sampling(a, spacing=spacing, start_idx=start_idx)
             sample_ind, _ = torch.sort(sample_ind) #this will make postprocessing easier
             a_, v_, l_, m_ = a[sample_ind], v[sample_ind], l[sample_ind], m[sample_ind]