diff --git a/docs/conf.py b/docs/conf.py
index 23c2b713..eba90be8 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -111,6 +111,7 @@
 autodoc_mock_imports = ["ete4"]
 intersphinx_mapping = {
     "anndata": ("https://anndata.readthedocs.io/en/stable/", None),
+    "decoupler": ("https://decoupler.readthedocs.io/en/latest/", None),
     "mudata": ("https://mudata.readthedocs.io/stable/", None),
     "matplotlib": ("https://matplotlib.org/stable/", None),
     "numpy": ("https://numpy.org/doc/stable/", None),
diff --git a/docs/tutorials/notebooks b/docs/tutorials/notebooks
index 83cb3eef..7ae61d53 160000
--- a/docs/tutorials/notebooks
+++ b/docs/tutorials/notebooks
@@ -1 +1 @@
-Subproject commit 83cb3eef2ab399bf2448dec5c72f6ad442b02abb
+Subproject commit 7ae61d535361c00e845c39217d513c049f340241
diff --git a/pertpy/tools/_differential_gene_expression/_base.py b/pertpy/tools/_differential_gene_expression/_base.py
index 61747968..003c6c39 100644
--- a/pertpy/tools/_differential_gene_expression/_base.py
+++ b/pertpy/tools/_differential_gene_expression/_base.py
@@ -83,15 +83,7 @@ def compare_groups(
             >>> adata = pt.dt.zhang_2021()
             >>> adata.layers["counts"] = adata.X.copy()
             >>> ps = pt.tl.PseudobulkSpace()
-            >>> pdata = ps.compute(
-            ...     adata,
-            ...     target_col="Patient",
-            ...     groups_col="Cluster",
-            ...     layer_key="counts",
-            ...     mode="sum",
-            ...     min_cells=10,
-            ...     min_counts=1000,
-            ... )
+            >>> pdata = ps.compute(adata, target_col="Patient", groups_col="Cluster", layer_key="counts", mode="sum")
             >>> edgr = pt.tl.EdgeR(pdata, design="~Efficacy+Treatment")
             >>> res_df = edgr.compare_groups(pdata, column="Efficacy", baseline="SD", groups_to_compare=["PR", "PD"])
         """
@@ -163,15 +155,7 @@ def plot_volcano(  # pragma: no cover # noqa: D417
             >>> adata = pt.dt.zhang_2021()
             >>> adata.layers["counts"] = adata.X.copy()
             >>> ps = pt.tl.PseudobulkSpace()
-            >>> pdata = ps.compute(
-            ...     adata,
-            ...     target_col="Patient",
-            ...     groups_col="Cluster",
-            ...     layer_key="counts",
-            ...     mode="sum",
-            ...     min_cells=10,
-            ...     min_counts=1000,
-            ... )
+            >>> pdata = ps.compute(adata, target_col="Patient", groups_col="Cluster", layer_key="counts", mode="sum")
             >>> edgr = pt.tl.EdgeR(pdata, design="~Efficacy+Treatment")
             >>> edgr.fit()
             >>> res_df = edgr.test_contrasts(
@@ -538,15 +522,7 @@ def plot_paired(  # pragma: no cover # noqa: D417
             >>> adata = pt.dt.zhang_2021()
             >>> adata.layers["counts"] = adata.X.copy()
             >>> ps = pt.tl.PseudobulkSpace()
-            >>> pdata = ps.compute(
-            ...     adata,
-            ...     target_col="Patient",
-            ...     groups_col="Cluster",
-            ...     layer_key="counts",
-            ...     mode="sum",
-            ...     min_cells=10,
-            ...     min_counts=1000,
-            ... )
+            >>> pdata = ps.compute(adata, target_col="Patient", groups_col="Cluster", layer_key="counts", mode="sum")
             >>> edgr = pt.tl.EdgeR(pdata, design="~Efficacy+Treatment")
             >>> edgr.fit()
             >>> res_df = edgr.test_contrasts(
@@ -704,15 +680,7 @@ def plot_fold_change(  # pragma: no cover # noqa: D417
             >>> adata = pt.dt.zhang_2021()
             >>> adata.layers["counts"] = adata.X.copy()
             >>> ps = pt.tl.PseudobulkSpace()
-            >>> pdata = ps.compute(
-            ...     adata,
-            ...     target_col="Patient",
-            ...     groups_col="Cluster",
-            ...     layer_key="counts",
-            ...     mode="sum",
-            ...     min_cells=10,
-            ...     min_counts=1000,
-            ... )
+            >>> pdata = ps.compute(adata, target_col="Patient", groups_col="Cluster", layer_key="counts", mode="sum")
             >>> edgr = pt.tl.EdgeR(pdata, design="~Efficacy+Treatment")
             >>> edgr.fit()
             >>> res_df = edgr.test_contrasts(
@@ -791,15 +759,7 @@ def plot_multicomparison_fc(  # pragma: no cover # noqa: D417
             >>> adata = pt.dt.zhang_2021()
             >>> adata.layers["counts"] = adata.X.copy()
             >>> ps = pt.tl.PseudobulkSpace()
-            >>> pdata = ps.compute(
-            ...     adata,
-            ...     target_col="Patient",
-            ...     groups_col="Cluster",
-            ...     layer_key="counts",
-            ...     mode="sum",
-            ...     min_cells=10,
-            ...     min_counts=1000,
-            ... )
+            >>> pdata = ps.compute(adata, target_col="Patient", groups_col="Cluster", layer_key="counts", mode="sum")
             >>> edgr = pt.tl.EdgeR(pdata, design="~Efficacy+Treatment")
             >>> res_df = edgr.compare_groups(pdata, column="Efficacy", baseline="SD", groups_to_compare=["PR", "PD"])
             >>> edgr.plot_multicomparison_fc(res_df)