Bioinformatics Department, OMass Therapeutics, Oxford Business Park, ARC, Oxford OX4 2GX, United Kingdom.
Bioinformatics. 2023 Aug 1;39(8). doi: 10.1093/bioinformatics/btad441.
Open Target Genetics is a comprehensive resource portal that offers variant-centric statistical evidence, enabling the prioritization of causal variants and the identification of potential drug targets. The portal uses GraphQL technology for efficient data query and provides endpoints for programmatic access for R and Python users. However, leveraging GraphQL for data retrieval can be challenging, time-consuming, and repetitive, requiring familiarity with the GraphQL query language and processing outputs in nested JSON (JavaScript Object Notation) format into tidy data tables. Therefore, developing open-source tools are required to simplify data retrieval processes to integrate valuable genetic information into data-driven target discovery pipelines seamlessly.
otargen is an open-source R package designed to make data retrieval and analysis from the Open Target Genetics portal as simple as possible for R users. The package offers a suite of functions covering all query types, allowing streamlined data access in a tidy table format. By executing only a single line of code, the otargen users avoid the repetitive scripting of complex GraphQL queries, including the post-processing steps. In addition, otargen contains convenient plotting functions to visualize and gain insights from complex data tables returned by several key functions.
otargen is available at https://amirfeizi.github.io/otargen/.
Open Target Genetics 是一个综合性的资源门户，提供以变体为中心的统计证据，用于优先考虑因果变体，并确定潜在的药物靶点。该门户使用 GraphQL 技术进行高效的数据查询，并为 R 和 Python 用户提供了程序化访问的端点。然而，利用 GraphQL 进行数据检索可能具有挑战性、耗时且重复，需要熟悉 GraphQL 查询语言，并将嵌套的 JSON（JavaScript 对象表示法）格式的处理输出转换为整洁的数据表。因此，需要开发开源工具来简化数据检索过程，以便将有价值的遗传信息无缝集成到数据驱动的目标发现管道中。
otargen 是一个开源的 R 包，旨在为 R 用户尽可能简化从 Open Target Genetics 门户检索和分析数据的过程。该包提供了一系列涵盖所有查询类型的功能，允许以整洁的表格格式进行流线型的数据访问。通过仅执行一行代码，otargen 用户可以避免重复编写复杂的 GraphQL 查询及其后处理步骤。此外，otargen 包含方便的绘图功能，可用于可视化和从几个关键功能返回的复杂数据表中获取见解。
otargen 可在 https://amirfeizi.github.io/otargen/ 获得。
