Kibio

Kibio provides scalable, Elasticsearch-backed storage and search for heterogeneous biological and multi-omics datasets to enable integrative analysis and standardized data exchange.


Key Features:

  • Scalability and Adaptability: Built on Elasticsearch to handle large volumes of diverse biological data with scalable search and storage capabilities.
  • Uniform Data Exchange Model: Applies a consistent model for data exchange to organize datasets into a standardized, interoperable format.
  • Decentralized, Searchable Organization: Structures data in a decentralized and searchable manner to facilitate integration and cross-dataset queries.
  • Programmatic Access via KibioR: Integrates with the KibioR package to support programmatic pull, push, and search operations against Kibio datasets and Elasticsearch-based databases.

Scientific Applications:

  • Multi-omics integration: Enables combining heterogeneous omics datasets for integrative analyses across molecular layers.
  • Drug characterization: Supports data aggregation and search workflows used in drug characterization studies.
  • miRNA analysis: Facilitates storage and retrieval of miRNA-related datasets for downstream analysis.
  • Pathway identification: Supports querying and integration of datasets used in pathway identification and analysis.

Methodology:

Kibio employs Elasticsearch as its core technology, implements a uniform data exchange model, organizes data into a decentralized and searchable structure, and integrates with KibioR for programmatic pull/push/search of Elasticsearch-based databases.

Topics

Details

License:
GPL-2.0
Tool Type:
library, workflow
Programming Languages:
R
Added:
10/4/2021
Last Updated:
10/4/2021

Operations

Publications

Ongaro-Carcy R, Scott-Boyer M, Dessemond A, Belleau F, Leclercq M, Périn O, Droit A. KibioR & Kibio: a new architecture for next-generation data querying and sharing in big biology. Bioinformatics. 2021;37(17):2706-2713. doi:10.1093/bioinformatics/btab157. PMID:33751043.

PMID: 33751043
Funding: - L’Oreal Research and Innovation chair in Digital Biology and Natural Sciences and Engineering Research Council of Canada [NSERC: CG118883

Links