otargen: GraphQL-based R package for tidy data accessing and processing from Open Targets Genetics.

Area of Science:

• Genetics
• Bioinformatics
• Pharmacogenomics

Background:

• Open Target Genetics provides variant-centric statistical evidence for prioritizing causal variants and identifying drug targets.
• GraphQL technology facilitates efficient data querying but presents challenges in data retrieval and processing for R and Python users.
• Complex GraphQL queries and nested JSON outputs require significant effort to integrate genetic data into target discovery workflows.

Purpose of the Study:

• To develop an open-source R package that simplifies data retrieval and analysis from the Open Target Genetics portal.
• To provide R users with a streamlined approach to access genetic information, avoiding complex GraphQL scripting.
• To facilitate the integration of genetic data into data-driven drug target discovery pipelines.

Main Methods:

• Development of the open-source R package 'otargen'.
• Implementation of functions to cover all query types available on the Open Target Genetics portal.
• Design of functions to return data in a tidy table format for easy analysis.
• Inclusion of plotting functions for data visualization.

Main Results:

• The 'otargen' R package offers a simplified, single-line code solution for accessing Open Target Genetics data.
• Users can retrieve genetic data in a tidy format, bypassing complex GraphQL queries and JSON processing.
• The package includes convenient plotting functions for visualizing complex genetic datasets.
• Streamlined data access accelerates the process of identifying potential drug targets.

Conclusions:

• 'otargen' significantly reduces the complexity and time required for R users to leverage Open Target Genetics data.
• The package enhances the integration of genetic evidence into drug discovery pipelines.
• This open-source tool democratizes access to valuable genetic insights for a wider research community.