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+Usage
+=====
+
+.. _installation:
+
+Installation
+------------
+
+To use MultiVelo, first install it using pip or conda:
+
+.. code-block:: console
+
+   $ pip install multivelo
+
+or
+
+.. code-block:: console
+
+   $ conda install -c bioconda multivelo
+
+Demo
+----
+
+A tutorial showing how to run MultiVelo can be found in `multivelo_demo <https://github.com/welch-lab/MultiVelo/tree/main/multivelo_demo>`_.
+
+We use the embryonic E18 mouse brain from 10X Multiome as an example.
+
+CellRanger output files can be downloaded from 
+`10X website <https://www.10xgenomics.com/resources/datasets/fresh-embryonic-e-18-mouse-brain-5-k-1-standard-1-0-0>`_. 
+Crucially, the filtered feature barcode matrix folder, ATAC peak annotations TSV, and the feature 
+linkage BEDPE file in the secondary analysis outputs folder will be needed in this demo.
+
+You can download the processed data that we used for this analysis if you want to run the example yourself. 
+Unspliced and spliced counts, as well as cell type annotations can be downloaded from the MultiVelo GitHub page. 
+We provide the cell annotations for this dataset in "cell_annotations.tsv". 
+We also provide the nearest neighbor graph used to smooth chromatin accessibility values in the GitHub folder "seurat_wnn", 
+which contains a zip file of three files: "nn_cells.txt", "nn_dist.txt", and "nn_idx.txt". Please unzip the archive after downloading. 
+The R script used to generate these files can also be found in the same folder.
+