Mots-Clés
Multiomics data, web application, RShiny, user interface, immuno oncology
Description
Development of a R shiny application for multi-omics data analysis in the field of Immuno-oncology
Company: Explicyte / Dr Alban BESSEDE & Dr Jean Philippe GUEGAN
Context: The field of biology is witnessing an unprecedented deluge of data driven by the rapid advancement of high-throughput technologies. This surge of multi-omics data, encompassing genomics, transcriptomics, proteomics, and metabolomics, presents a goldmine of information for biologists. However, analyzing this complex data often requires coding knowledge and command-line interfaces, intimidating for biologists with limited computational experience. This creates a bottleneck, hindering researchers from directly investigating their data and potentially delaying scientific progress. User-friendly data analysis applications are urgently needed to empower non-bioinformatician biologists to unlock the potential of multi-omics data.
Objective: We aim at developing an intuitive R shiny application featuring clear, visual interfaces with minimal technical jargon and tooltips for guidance. This application will offer pre-configured workflows for common analysis tasks, like differential expression analysis or pathway enrichment analysis, and will be interactive to allow biologists to explore data relationships visually through customizable charts and graphs. Finally, the application will generate clear and concise reports with visualizations, eliminating the need for manual data manipulation and interpretation.
Methodology: The user interface (UI) will be built using R Shiny, a web application framework for R. The UI will prioritize clarity and ease of use, featuring a logical layout with clear tabs or sections for data upload, analysis selection, and result visualization together with Interactive widgets like drop-down menus, sliders, and checkboxes for user input and parameter selection. Tooltips and help menus providing brief explanations for each option will be available to help the user. The application will offer a variety of pre-configured analysis workflows, catering to common multi-omics tasks such as differential expression analysis, pathway enrichment and correlation analysis to explore relationships between different omics layers. Interactive visualizations will be a key component, allowing users to explore data patterns visually through customizable charts and graphs, heatmaps or networks. The server-side logic of the application will be written in R. The application will leverage existing R packages for statistical analysis and data manipulation. Popular choices include packages like DESeq2 for differential expression, clusterProfiler for pathway enrichment, and ggplot2 for creating informative visualizations. The completed R Shiny application will be packaged for deployment on a in-house server, allowing biologists to access it remotely through a web browser.
Skills (required or to be developed):
- Strong foundation in R and understanding of R shiny framework
- Knowledge of R packages for data science and omics analysis (DESeq2, clusterProfiler…)
- Mastery of basic and multivariate statistics is required.
- Familiarity with web technologies like HTML, CSS, and Javascript (UI customization)
- Well-organized with demonstrated ability to prioritize actions, work simultaneously on several tasks to generate high quality deliverables according to defined timelines.
- Enthusiasm and high motivation, with integrity and strong interpersonal and organizational skills.
- Possess a theoretical understanding of the algorithms used for data analysis and conduct an independent literature review to be at the forefront of the latest developments and data analysis methods.