fixed index and clustering workflow

DendrouLab · Nov 27, 2023 · 73c85a4 · 73c85a4
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diff --git a/docs/tutorials/index.md b/docs/tutorials/index.md
@@ -4,12 +4,12 @@ Tutorials
 Check out the following tutorials which take you through some common analysis steps with Panpipes:
 
 
-- [Ingest pipeline](https://panpipes-tutorials.readthedocs.io/en/latest/ingesting_data/Ingesting_data_with_panpipes.html)
-- [Preprocessing pipeline](https://panpipes-tutorials.readthedocs.io/en/latest/filtering_data/filtering_data_with_panpipes.html)
-- [Integration pipeline](https://panpipes-tutorials.readthedocs.io/en/latest/uni_multi_integration/Integrating_data_with_panpipes.html)
-- [Clustering pipeline](https://panpipes-tutorials.readthedocs.io/en/latest/clustering/clustering_tutorial.html)
-- [Reference mapping](https://panpipes-tutorials.readthedocs.io/en/latest/refmap_pancreas/Reference_mapping.html)
-- [Visualization pipeline](https://panpipes-tutorials.readthedocs.io/en/latest/visualization/vis_with_panpipes.html)
+- [Ingest workflow](https://panpipes-tutorials.readthedocs.io/en/latest/ingesting_data/Ingesting_data_with_panpipes.html)
+- [Preprocessing workflow](https://panpipes-tutorials.readthedocs.io/en/latest/filtering_data/filtering_data_with_panpipes.html)
+- [Integration workflow](https://panpipes-tutorials.readthedocs.io/en/latest/uni_multi_integration/Integrating_data_with_panpipes.html)
+- [Clustering workflow](https://panpipes-tutorials.readthedocs.io/en/latest/clustering/clustering_tutorial.html)
+- [Reference mapping workflow](https://panpipes-tutorials.readthedocs.io/en/latest/refmap_pancreas/Reference_mapping.html)
+- [Visualization workflow](https://panpipes-tutorials.readthedocs.io/en/latest/visualization/vis_with_panpipes.html)
 
 Spatial analysis:
 

diff --git a/docs/workflows/clustering.md b/docs/workflows/clustering.md
@@ -6,9 +6,10 @@ The panpipes clustering pipeline runs the following steps:
 ```
 neighbors:
   rna:
-    use_existing: False
-    # number of Principal Components to calculate for neighbours and umap:
-    dim_red: X_harmony (or any reduced dimensional represenation in your MuData object)
+    use_existing: True
+    # which representation in .obsm to use for nearest neighbors
+    # if dim_red=X_pca and X_pca not in .obsm, will be computed with default parameters
+    dim_red: X_pca
     #how many components to use for clustering
     n_dim_red: 30
     # number of neighbours
@@ -43,4 +44,6 @@ neighbors:
 ## Expected structure of MuData object
 The ideal way to run `panpipes clustering` is to use the output mudata file from `panpipes preprocess` or `panpipes integration`, as this will make sure the MuData object has correctly names layers and slots. 
 
-The bare minimum MuData object required is normalised data in the X slot of each modality,  a sample_id column in each slot of the obs and the outer obs, and the layers indicated in the find_markers section of the yml.
+The bare minimum MuData object required is normalised data in the X slot of each modality,  a sample_id column in each slot of the obs and the outer obs, and the layers indicated in the find_markers section of the yml.
+
+Check the [clustering tutorial](https://panpipes-tutorials.readthedocs.io/en/latest/clustering/clustering_tutorial.html) for an example of how to run the workflow.