Metacells Vignettes

These vignettes give examples for using the metacells, specifically version 0.9.0. They are not meant as a comprehensive documentation of all the features, and the data contained in them should not be used for any serious analysis. They are just examples of the processes that one typically uses when using the metacells package for analysis of scRNA-seq data.

View the results

You can directly view the vignettes here:

• One Pass Process
• Iterative Process
• Projection Process

Re-run the vignettes

You will need the following software to be installed:

• The Python metacells package, of course.

• The Python seaborn package for generating graphs. Just pip install seaborn.

• An R environment.

• The R MCView package installed in it. See the installation instructions in the package (it is not a standard CRAN package).

• And, of course, a Jupyter setup that can access both the Python and R environments.

To get the Jupyter notebook sources, just git clone this repository. You can adapt the notebooks to use your own data, of course. If you want to reproduce them, you'll need to get the data as well:

• First, cd into the cloned repository.

• Then, wget https://metacells-vignette.s3.eu-west-1.amazonaws.com/blobs.tgz to get the data files. This will download ~1GB of data.

• Finally, tar xvzf blobs.tgz which will extract the data files into the blobs directory, requiring ~6GB of disk space.

The data in these files comes from the following sources:

• Human Cell Atlas Bone Marrow Data from here.

• Blood aging data from here.

License (MIT)

Copyright © 2023 Weizmann Institute of Science

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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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