bioRxivBioinformaticsPreprint
Genomic Annotation Infrastructure (GAIn): Pipelines and Resource Repositories for Annotating Variants, Positions, and Regions
Murat CokoliD, Lubomir Chorbadjiev, Yoon-ha Lee, Minal JamsandekariD, Ilina Gergova, Ivo TodoroviD, Ivan H. IossifoviD
Abstract
Interpretation of genomic variants, positions, and regions depends on reliable annotation--adding evidence such as predicted effect, conservation, population frequency, and gene-level context--yet the underlying resources are numerous, versioned, and assembly-specific. We present the Genomic Annotation Infrastructure (GAIn), a platform that generates transparent, reproducible annotations via declarative pipelines that define annotation tasks as ordered lists of components, called annotators, that produce annotation attributes using genomic resources from Genomic Resource Repositories (GRRs). We provide two public GRRs: a main repository containing more than 250 heterogeneous genomic resources, and a separate GRR-ENCODE repository containing resources derived from thousands of ENCODE (Encyclopedia of DNA Elements) project experiments. Users can use the annotation pipelines we made available, author custom annotation pipelines, and execute annotation tasks with these pipelines via GAIns web and command-line interfaces. The web interface can be used without any setup, but it relies on shared computational infrastructure and imposes limits on the size of annotation tasks. The command-line interface requires setup but supports arbitrarily large annotation tasks through simple-to-use parallelization and offers a broader set of features. For example, command-line GAIn can be extended by using custom GRRs or creating custom annotators via its plugin architecture. In addition, GAIns re-annotation feature, which updates annotations as they evolve, substantially simplifies maintaining annotations in a large genomics analysis project. GAIns resource management, explicit versioning, and pipeline abstraction provide an auditable, maintainable, and efficient foundation for modern genomic annotation across reference assemblies and use cases.
- assay: whole-genome sequencing
- assay: whole-exome sequencing
- research focus: variant calling
- research focus: variant effect prediction
- research focus: database / resource
- approach: statistical model
- Citations
- 0
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