Consortia

Effective data mangement and seamless collaboration

The UniApp’s data library feature serves as the backbone of research consortia workflows, offering a centralized repository to store and index diverse datasets. Say goodbye to the hassle of scattered data files, unrecallable versioning and disjointed information. With its intuitive interface and advanced indexing capabilities, the UniApp platform makes it easy for research teams to maintain a clear overview of available data for their collaborative studies across sites, teams and team members.

Users can easily annotate and search for datasets within the platform, streamlining data discovery and utilization. Comprehensive metadata editing and harmonization capabilities ensure data integrity and reproducibility, empowering researchers to confidently build upon existing datasets.

Additionally, the UniApp also simplifies access management and the setup of dedicated workspaces for sub-projects or teams. With just a few clicks, you can assign roles and permissions, ensuring that team members have the appropriate level of access to data and tools. This streamlined process facilitates collaboration and keeps your team’s workflow efficient and secure.

Unify methodologies and analysis tools at scale for robust results

Ensuring consistency in methodologies and interoperability of results is among the key challenges faced by large-scale biomedical research consortia. The UniApp effectively addresses these challenges by providing a unified platform for data analysis and data visualizations. By integrating a single analysis tool with a standardized research protocol or workflow, the UniApp supports methodological consistency for interpreting and integrating results from diverse datasets and multiple sources. This unified approach streamlines data integration and analysis, making it easier to derive meaningful insights from complex research.

To handle the extensive data volumes typical of such studies, the UniApp offers a comprehensive suite of features and built-in algorithms. Researchers can perform a wide range of analyses, from basic exploratory studies to advanced meta-analyses, without needing to switch between multiple tools, download additional packages, or acquire coding skills. Additionally, all analysis steps are automatically recorded, enhancing the reproducibility and consistency of results. This centralized approach mitigates the inconsistencies and errors that often arise from using disparate tools or online packages, ensuring that results are comparable and reliable across different teams.

UniApp’s intuitive interface allows users to focus on interpreting results rather than mastering technical skills. With an extensive library of over 40 customizable data visualization options, users can either create highly tailored visualizations or leverage centrally defined color templates to maintain consistency between outputs. This ease of use not only streamlines the analysis process but also reinforces reproducibility and reliability, which are essential for validating findings and ensuring comparability across various research teams.

Specific technical or data-driven research skills addressed

Unicle’s consulting services for research consortia focus on tool development and capability building to optimize data analysis and enhance collaboration. For consortia with unique analytical requirements, our technical development consultants can create new functionalities, automated workflows, or algorithms tailored to the project on the UniApp. Additionally, our development team can facilitate the integration of in-house developed algorithms into the UniApp, ensuring these tools can be used effectively across all teams.

Another key aspect of Unicle’s consulting support is capability building within research teams, through targeted workshops and seminars. These training sessions are designed to upskill researchers and analysts, ensuring they can fully leverage UniApp’s capabilities for data analysis and visualization. By equipping team members with the necessary knowledge and skills, these sessions foster a unified approach to data management and analysis across the consortium. Furthermore, they support researchers in transforming data into relevant and actionable insights, ready for presentation or scientific publication.

Integrated scalable solution, built on the shoulders of tech giants

The UniApp platform is designed with scalability in mind, combining top-ranked technology solutions to address the evolving needs of large-scale biomedical research and pharmaceutical projects. Built on the powerful R and R Shiny framework, the UniApp aligns perfectly with the core standards of these sectors, where R is a fundamental tool for statistical analysis. The UniApp stands out as one of the most extensive and complex production-ready R/Shiny applications available today, combining R’s advanced statistical computing with Shiny’s interactive web interface to deliver a robust and user-friendly platform for comprehensive data analysis and visualization.

To harness the benefits of trusted and scalable solutions, the UniApp is based upon the Google Cloud Platform. This enables to dynamically scale computational resources to meet the demands of intensive data analysis, without the need for researchers to invest in costly local hardware investments. This integration not only facilitates the effective management of increasing data volumes but also enhances data security and protection incorporated with the Google Cloud Platform. Additional data safeguards have been added to the UniApp platform by integrating well-established data protection solutions of Auth0 and NGINX.

To boost data processing, the UniApp has incorporated Nextflow, a leading tool for managing vast amounts of data and streamlining complex data processing pipelines. The use of Kubernetes further optimizes resource utilization, ensuring efficient allocation and maintenance of computational resources. This powerful combination of technologies positions UniApp as a premier platform for scalable data analysis in a secured environment, driving innovation and discovery in the biomedical research community.