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theislab · Dec 5, 2024 · 16f6d4a · 16f6d4a
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diff --git a/tutorials/300_spatial_alignment.ipynb b/tutorials/300_spatial_alignment.ipynb
@@ -20,7 +20,7 @@
     ":::\n",
     "\n",
     ":::{seealso}\n",
-    "- TODO: link to other tutorials\n",
+    "- If the spatial coordinates are only available for one dataset, see {doc}`400_spatial_mapping` on how to transfer gene expression from single-cell data to spatial data.\n",
     ":::"
    ]
   },
@@ -375,7 +375,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "moscot_new",
+   "display_name": "moscot",
    "language": "python",
    "name": "python3"
   },
@@ -389,7 +389,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.12.0"
   }
  },
  "nbformat": 4,

diff --git a/tutorials/400_spatial_mapping.ipynb b/tutorials/400_spatial_mapping.ipynb
@@ -18,7 +18,7 @@
     ":::\n",
     "\n",
     ":::{seealso}\n",
-    "- TODO: link to other tutorials\n",
+    "- If spatial coordinates are available for multiple datasets, see {doc}`300_spatial_alignment` on how to align spatial transcriptomics data, integrating both gene expression and spatial similarity.\n",
     ":::"
    ]
   },
@@ -284,7 +284,7 @@
    "source": [
     "### Solve the {class}`~moscot.problems.space.MappingProblem`\n",
     "\n",
-    "We are now ready to {meth}`~moscot.problems.space.MappingProblem.solve` the problem. The most important parameter to take into account is the `alpha` value, which balances the weight of each loss (\"unique\" vs. \"shared\" spaces). With alpha close to $0$, the \"shared\" space loss is weighted more, with alpha close to $1$, the \"unique\" space loss is balanced more. For the purpose of this example, we'll use `alpha=0.5` but we suggest to increase it if only a few features are present. It should take maximum one minute on a laptop."
+    "We are now ready to {meth}`~moscot.problems.space.MappingProblem.solve` the problem. The most important parameter to take into account is the `alpha` value, which balances the weight of each loss (\"unique\" vs. \"shared\" spaces). With alpha close to $0$, the \"shared\" space loss is weighted more, with alpha close to $1$, the \"unique\" space loss is weighted more. For the purpose of this example, we'll use `alpha=0.5` but we suggest to increase it if only a few features are present. It should take maximum one minute on a laptop."
    ]
   },
   {
@@ -404,7 +404,7 @@
    "metadata": {},
    "source": [
     "Finally, we provide a helper function to compute \"spatial correspondence\" - {meth}`~moscot.problems.space.MappingProblem.spatial_correspondence`, that is, the average expression distance at increasing spatial distance, as originally proposed by *NovoSpaRc* {cite}`nitzan:19`. \n",
-    "If a strong spatial correspondence is observed (as in this case) it can be useful to increase the `alpha` value."
+    "If a strong spatial correspondence is observed (as in this case) it can be useful to add weight to the spatial coordinates by increasing the `alpha` value."
    ]
   },
   {