Tabula Muris Senis on AWS
The Tabula Muris Senis dataset was generated by the Chan Zuckerberg Biohub and made available for anyone to use via Amazon S3.

Tabula Muris Senis is a comprehensive compendium of single cell transcriptomic data from the model organism *Mus musculus* comprising more than 500,000 cells from 18 organs and tissues across the mouse lifespan. We discovered cell-specific changes occurring across multiple cell types and organs, as well as age related changes in the cellular composition of different organs. Using single-cell transcriptomic data we were able to assess cell type specific manifestations of different hallmarks of aging, such as senescence, changes in the activity of metabolic pathways, depletion of stem-cell populations, genomic instability and the role of inflammation as well as other changes in the organism’s immune system. Tabula Muris Senis provides a wealth of new molecular information about how the most significant hallmarks of aging are reflected in a broad range of tissues and cell types.See: https://www.biorxiv.org/content/10.1101/661728v2

This rich collection of annotated cells will be a useful resource for:

Defining gene expression in previously poorly-characterized cell populations.
Validating findings in future targeted single-cell studies.
Developing of methods for integrating datasets (eg between the FACS and droplet experiments), characterizing batch effects, and quantifying the variation of gene expression in many cell types between organs and animals.
Since Summer 2019, Tabula Muris Senis data have been made available to all users free of charge. AWS has made the data freely available on Amazon S3 so that anyone can download the resource to perform analysis and advance medical discovery without needing to worry about the cost of storing Tabula Muris Senis data or the time required to download it.

Contact
If you have questions about the data, you can create an Issue at the project repo on GitHub.

License
There are no restrictions on the use of data received from the Chan Zuckerberg Biohub, unless expressly identified prior to or at the time of receipt.