OTxplorer-R: Discover Targets With R & Open Targets Data

Hey guys! Let's dive into the exciting world of target discovery with the OTxplorer-R package. This tool is a game-changer for researchers looking to explore the vast landscape of drug targets, diseases, and drugs using the treasure trove of data from the Open Targets Platform. If you're ready to level up your research game, buckle up and let's get started!

Short Description

Imagine having a visual tool that lets you navigate the intricate web of relationships between drug targets, diseases, and drugs. That's precisely what the Target Graph Explorer does! It transforms complex data into an interactive network, allowing users to uncover hidden connections and prioritize targets visually. Forget sifting through endless tables and search results; this tool, built as an R Shiny app, brings a whole new level of intuition to target discovery.

Objective/Problem Statement

The Open Targets Platform is a goldmine of data, but accessing and visualizing relationships can be challenging. Currently, there isn't a lightweight, visual interface to explore the connections between targets, diseases, and drugs as an interconnected graph. This project addresses this gap by creating an interactive network visualization tool that empowers users to explore evidence-based target associations and identify novel therapeutic opportunities in a user-friendly manner. This is super beneficial for experimental biologists, early-career researchers, and anyone eager to pinpoint potential therapeutic targets using Open Targets data quickly.

This is a critical need because, let's be honest, staring at spreadsheets isn't exactly the most inspiring way to find the next breakthrough. We need tools that make the process more intuitive and accessible, especially for those just starting their journey in drug discovery. An interactive graph is a total game-changer, making it easier to spot patterns and connections that might otherwise be missed. The goal here is to lower the barrier to entry and empower more researchers to make meaningful discoveries.

Consider this: A researcher is investigating a particular disease and wants to find potential drug targets. Instead of manually searching databases and compiling lists, they can use OTxplorer-R to visualize the connections between the disease and various targets. They can see which targets have strong evidence associations, which drugs are already being used to target them, and even identify potential targets that haven't been explored yet. This saves time, reduces the risk of overlooking crucial information, and accelerates the discovery process. How cool is that?

How it uses Open Targets Platform

OTxplorer-R leverages the Open Targets Platform in several key ways:

• It uses the Open Targets Platform API (GraphQL) to fetch data on target-disease associations, evidence scores, and known drugs.
• It visualizes this data as an interactive network to reveal hidden or interesting connections.
• Users can search for genes or diseases of interest and see their connections in real-time.
• The tool allows filtering results based on evidence type or strength, ensuring users can focus on the most relevant data.
• It even supports the upload of custom gene lists for contextual exploration, making it super flexible for various research needs.

Think of it as having a powerful magnifying glass that allows you to zoom in on specific areas of interest within the vast landscape of drug targets. By fetching data directly from the Open Targets Platform API, OTxplorer-R ensures that users are always working with the most up-to-date information. The interactive network visualization is where the magic happens. It's not just about seeing the data; it's about experiencing it. The ability to filter results based on evidence type and strength adds another layer of precision, allowing researchers to fine-tune their searches and identify the most promising leads.

Imagine a researcher who has a list of genes suspected to be involved in a particular disease. They can upload this list into OTxplorer-R and immediately see how these genes connect to known drug targets, other diseases, and even specific drugs. This contextual exploration can spark new hypotheses and reveal unexpected connections, potentially leading to groundbreaking discoveries. It’s all about making the data work for you, not the other way around.

Technologies/Tools

Here's a peek under the hood at the technologies and tools that power OTxplorer-R:

• App Framework: R Shiny – This makes the app interactive and user-friendly.
• Visualization: visNetwork, igraph – These libraries handle the heavy lifting of creating the network visualizations.
• Data Wrangling: tidyverse, jsonlite – These tools are essential for cleaning and organizing the data pulled from the API.
• API: Open Targets GraphQL API – This is the gateway to the wealth of data within the Open Targets Platform.
• Code Hosting: GitHub (Apache 2.0) – The code is open-source, making it accessible and collaborative.

Let's break this down a bit. R Shiny is the star player here, providing the framework for building an interactive web application using R. This means that OTxplorer-R can be accessed through a web browser, making it super convenient for researchers to use. visNetwork and igraph are the dynamic duo for creating stunning network visualizations. They allow users to see the connections between targets, diseases, and drugs in a clear and intuitive way. The tidyverse and jsonlite are the unsung heroes, working behind the scenes to ensure that the data is clean, organized, and ready for analysis.

The use of the Open Targets GraphQL API is crucial because it allows OTxplorer-R to tap directly into the platform's vast data resources. This ensures that the tool always has access to the latest information, which is essential for making informed decisions. And last but not least, hosting the code on GitHub under the Apache 2.0 license means that OTxplorer-R is an open-source project. This fosters collaboration, encourages contributions from the community, and ensures that the tool remains accessible to researchers around the world. It’s all about building a tool that’s not only powerful but also sustainable and community-driven.

Expected Outcome/Deliverables

So, what can you expect from this project? Here's the rundown:

1. A working prototype of a visual exploration tool as an R Shiny app – Get ready to see the magic in action!
2. Interactive network visualization of target-disease-drug relationships – This is where you'll uncover those hidden connections.
3. Search and filtering capabilities – Find exactly what you're looking for with ease.
4. Open-source code on GitHub (Apache 2.0 license) – Dive into the code, contribute, and make it your own.
5. Documentation or user guide – No one likes getting lost, so there's a guide to help you navigate.
6. Presentation or demo of key features – See the tool in action and learn how to make the most of it.

These deliverables are all about providing a complete package for researchers. The working prototype is the tangible result of all the hard work, giving users a hands-on experience with the tool. The interactive network visualization is the heart of OTxplorer-R, allowing users to explore data in a way that's simply not possible with traditional methods. The search and filtering capabilities ensure that you can quickly find the information you need, without getting bogged down in irrelevant data.

By making the code open-source on GitHub, the project encourages collaboration and ensures that the tool can continue to evolve and improve over time. The documentation and user guide are essential for making OTxplorer-R accessible to a wide range of users, regardless of their technical expertise. And finally, the presentation or demo will showcase the tool's key features and demonstrate how it can be used to accelerate target discovery. It’s all about empowering researchers to make new discoveries and bring life-changing therapies to patients faster.

Labels

team: frontend team: data-science topic: platform-features topic: drug-development network-visualization target-discovery drug-repurposing open-targets-api

In conclusion, OTxplorer-R is poised to become an indispensable tool for researchers in the field of drug discovery. By combining the power of R Shiny with the wealth of data in the Open Targets Platform, this project is set to transform the way we explore and identify potential drug targets. So, stay tuned, and get ready to explore the exciting world of target discovery with OTxplorer-R!

For more information on the Open Targets Platform, check out their website: https://www.opentargets.org/