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Overview

Gemma (pronounced: Jemma) is database of curated and re-analyzed gene expression studies.

Key features:

Terms and Conditions

Please refer to the Terms and conditions page!

Glossary

You may encounter some of these terms when using Gemma.

Using the Gemma website

This section is currently undergoing revision.

Programmatic use of Gemma

Gemma has a RESTful API, documented here. There you will find all necessary information on how to interact with gemma programatically.

However, most users will find more convenient programmatic access to Gemma’s data and analyses via gemma.R (R/Bioconductor) and gemmapy (Python).

The R and Python packages offer similar functionality and have their own documentation and examples/vignettes. For convenience we have gathered some examples in both languages here.

Data sources

We are indebted to the many researchers who have made data publicly available. Lists of published papers that relate to the data included in Gemma are available here (full list) and here (search).

If your data is in Gemma, and your paper is not listed, please let us know.

Contact

If you find a problem or need help, you can file a new github issue, or contact us at pavlab-support@msl.ubc.ca.

Credits

Financial support

As of 2023, Gemma is primarily supported by a grant from NIMH, and additional support from NSERC and CFI, for which we are grateful!

Citing

If you use any of Gemma tools or data for your research, please cite one of the following papers:

Lim et al. Curation of over 10 000 transcriptomic studies to enable data reuse. Database, 2021

Zoubarev, A., et al., Gemma: A resource for the re-use, sharing and meta-analysis of expression profiling data. Bioinformatics, 2012.

Project lead: Paul Pavlidis, Ph.D.

Copyright © University of British Columbia