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JSON-based QC database for NGS statistics

License: Other

Scala 90.10% Shell 4.04% JavaScript 0.44% Makefile 1.42% CSS 0.69% HTML 0.02% Python 1.97% Batchfile 1.33%

sentinel's Introduction

Sentinel

Sentinel is a JSON-based database for next-generation sequencing statistics. Queries and submissions are all done via a RESTful HTTP API which is specified based on Swagger.

Requirements

Java 8 (must be set as the default java)
Scala 2.11.6
MongoDB 3.2 (running on localhost port 27017 for live development server)
Python 2.7 and Sphinx (only when building the documentation)

If MongoDB 3.2 is not available in your official package repository, you can install it from the vendor's repository following the instructions here.

Support

Report issues to the issue page. Fixes and feature suggestions are also welcome.

sentinel's People

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sentinel's Issues

Implement user deletion in /users

Also, this means deciding:

what happens to the user's uploaded run summaries (should they be deleted as well? should they be hidden?)
what happens to the user's user ID (can it be reused by someone else or not?)

Emit CSV from stat endpoints

For queries which result in many items, the JSON keys become redundant as they are repeated over and over again. There should be a way to easily build CSVs from the internal case classes.

Add patching support for `/references` endpoint

The patch should, for now, be limited to CRUD operations on refName.

Update sphinx documentation

The current documentation is still pre-split. This should be updated before the next official release.

Support `.dict` file upload in `/references` endpoint

This would involve:

Adding a dict file parser + testing
Adding a new POST /references endpoint + testing

Use MongoDB aggregation framework for computing statistics

Some of the statistics not computable by MongoDB 3.0's aggregation framework (e.g. standard deviation) can now be computed in MongoDB 3.2. We should look into how far it is possible to replace the current MapReduce approach with this instead, as MapReduce tend to be quite slow.

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