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...	...	@@ -26,6 +26,14 @@
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27	27	=== in the collab (beta) ===
28	28
	29	+* **Copy the collab drive to your drive space**
	30	+** Open the Drive from the left menu
	31	+** Select the folders 'pipeline' and 'datasets'
	32	+** Select 'Copy', and 'My Library' from the dropdown 'Other Libraries'
	33	+
	34	+* **Start a Jupyter Hub instance **
	35	+copy the URL below in a separate browser page: 'jupyterhub-preview.apps-dev.hbp.eu'
	36	+
29	29	* **Edit the config files**
30	30	Each stage has a config file to specify which analysis/processing blocks to execute and which parameters to use. General and specific information about the blocks and parameters can found in the README and config files. The default values are set for an example dataset (ECoG, anesthetized mouse, IDIBAPS [ref]).
31	31	** stage01_data_entry: [README.md](), [config.yaml]()
...	...	@@ -34,13 +34,9 @@
34	34	** stage04_wavefront_detection: [README.md](), [config.yaml]()
35	35	** stage05_wave_characterization: [README.md](), [config.yaml]()
36	36
37		-* **Start a Jupyter Hub instance **
38		-copy the URL below in a separate browser page
39		-[[jupyterhub-preview.apps-dev.hbp.eu>>jupyterhub-preview.apps-dev.hbp.eu]]
40		-
41	41	* **Follow the notebook**
42	42	In the jupyter hub, navigate to `drive/Shared with groups/Slow Wave Analysis Pipeline/pipeline/showcase_notebooks/run_snakemake_in_collab.ipynb`.
43		-Follow the notebook to install the required packages into your Python kernel, set the output path, and execute the pipeline with snakemake.
	47	+* Follow the notebook to install the required packages into your Python kernel, set the output path, and execute the pipeline with snakemake.
44	44	* **Coming soon**
45	45	** Use of KnowledgeGraph API
46	46	** Provenance Tracking