Custom Datasets for Mass UI - stjude/proteinpaint GitHub Wiki
This page contains draft content. Thank you for your patience as we make updates.
The information in this wiki is intended for experienced bioinformaticians and developers. Please note that the ProteinPaint team does not provide support or guidance for creating ETLs or formatting data source files unless a formal collaboration or contract is in place.
For details about contracts and licensing, please refer to the ProteinPaint licensing information from the St. Jude Office of Technology Licensing.
Please refer to the mass UI README for the technical description of the mass UI.
Before attempting, one must:
- Possess an understanding of docker containers. Refer to their documentation here for assistance.
- Create and maintain ETLs specific to one's usage
Please use our test data in this directory as an example of how to properly format data for the mass UI. This test data directory is mounted to the ppfull
and ppserver
containers.
Pull a pinned docker image version.
docker pull <image-name>@<digest>
Note: Pulling our latest published image may break your usage.
Download the reference and support files to run the container. Please see the instructions here for downloading the files. Note: This only includes hg19 and hg38 at this time.
Make container/dataset
and create a dataset js file. As a reference, see our test dataset configuration file.
For more options and descriptions, please see the type definitions for dataset files here. Note: At this time only js files are supported. Later this year, support will be extended to ts files.
Create a serverconfig.json
, similar to container/ci/serverconfig.json. Include the custom dataset in the appropriate genome object in the datasets array. Here's an example:
"genomes": [
{
"name": "hg38",
"species": "human",
"file": "./genome/hg38.js",
"datasets": [{
"name": "Custom",
"jsfile": "./dataset/custom.js"
}]
}
] ...
Use ./run.sh ppfull:latest
(or a pinned image version from our github repo) in the container directory.
A detailed description for running the docker container is available here.