- Course overview
- Search within this course
- What is the IMPC?
- How is IMPC data generated?
- Translating to other species and learning about human disease
- The home page of the IMPC website
- Searching for a gene of interest
- Gene pages
- Chart pages
- Searching for phenotypes
- Phenotype pages
- Late Adult data
- Image data
- Data downloads
- Try it yourself
- Quiz: check your learning
- Summary
- Your feedback
- Get help and support on the IMPC
- References
All materials are free cultural works licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, except where further licensing details are provided.
Data downloads
In some instances, instead of looking for data associated with a specific gene or phenotype, you may want to download all available data for all the mouse lines the IMPC has phenotyped or for a selection of genes. There are four ways to do this:
- Directly from the website: For the data associated with a specific gene or phenotype, look for the download buttons in gene and phenotype pages.
- The FTP site: You can download all data via the FTP site; please check the README files in the FTP directory and our non-programmatic data access documentation for more information on this.
- Batch Query Service: To get significant phenotype data for a selection of genes you can use the Batch Query functionality in the IMPC website.
- Programmatic access via the API: To get specific data for a selection of genes, please refer to our programmatic data access documentation for more information on how to do this. The Python package impc_api provides several helper functions that build upon the IMPC Solr API. For an interactive introduction to using Python to access the API, take a look at the Accessing Mouse Phenotypes and Disease Associations with the IMPC Solr API course. This course teaches you how to extract information from the IMPC Solr endpoints using the impc_api package that you can install with pip and provides practical examples that you can try out in Google Colab or your own Jupyter notebook.
