GAIn Python interface

This section describes GAIn as a Python library. Use it to work with GRR resources directly from your own scripts, to embed GAIn in your own code, to add a resource implementation, or to write an annotator plugin.

If you write pipeline YAML or a command line rather than Python, read the user pages instead: Genomic resources and repositories for resources and repositories, and Annotation infrastructure for pipelines and annotators. Everything in this section is Python.

The chapters build bottom-up, substrate before the things that consume it:

  1. Overview and examples — the place to start: it connects to a repository and walks through five end-to-end examples, from reading chromosome lengths to writing, registering and running a small annotator plugin.

  2. Genomic resources — the resource part of the declared API: the builders, repositories and resources, reference genomes, gene models, the three kinds of score, histograms, and the seam for adding a resource type.

  3. Annotators — the annotation part of the declared API: what an annotator receives and declares, the two classes an annotator is built on, the pipeline that drives it, and the entry-point group through which a package of your own becomes an annotator a pipeline can name.

  4. Task graph — the task graph: how a script builds a graph of tasks, runs it with a task executor, and lets a task cache skip the tasks that are already done.

  5. Complete module index — the complete generated API tree, for when you already know the name you are looking for.