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Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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GIANT API: an application programming interface for functional genomics.

Andrew M Roberts1, Aaron K Wong1, Ian Fisk1

  • 1Simons Center for Data Analysis, Simons Foundation, New York, NY 10010, USA.

Nucleic Acids Research
|April 22, 2016
PubMed
Summary
This summary is machine-generated.

The GIANT API offers researchers access to gene networks for predicting gene relationships and uncovering disease links. This tool aids in re-prioritizing genome-wide association study data using tissue-specific networks.

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Genomics

Background:

  • Genomic studies generate vast amounts of data.
  • Understanding gene function and interactions is crucial for disease research.
  • Tissue-specific gene networks provide context for biological processes.

Purpose of the Study:

  • To provide programmatic access to comprehensive gene interaction networks.
  • To offer tools for functional re-prioritization of genome-wide association study (GWAS) data.
  • To facilitate the discovery of disease-gene associations.

Main Methods:

  • Development of the GIANT API, adhering to REST architecture.
  • Integration of 144 human tissue-specific functional gene networks.
  • Inclusion of global functional networks for humans and six model organisms.
  • Implementation of the NetWAS computational tool for GWAS data re-prioritization.

Main Results:

  • The API provides scalable and accessible programmatic access to diverse gene networks.
  • Researchers can predict gene relationships and identify tissue-specific gene roles.
  • The NetWAS tool enables effective re-prioritization of GWAS results using network information.

Conclusions:

  • The GIANT API empowers biomedical researchers with advanced tools for genetic data analysis.
  • It facilitates the exploration of gene function across tissues and the identification of disease-related genes.
  • The freely available resource supports data analysis and visualization for a wide range of clients.