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GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal.
Lydia King1,2, Andrew Flaus3, Simone Coughlan1,2
1SFI Centre for Genomics Data Science, National University of Ireland, Galway, H91 TK33, Ireland.
HRB Open Research
|September 19, 2022
Summary
We developed GNOSIS, an R Shiny App, to help researchers easily explore cancer genomics data for prognostic markers. This tool simplifies complex analyses, supporting diagnostic and therapeutic discoveries.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Analyzing cancer consortia data from repositories like cBioPortal often requires advanced programming skills.
- Identifying novel genomic prognostic markers for diagnostic and therapeutic use is challenging.
Purpose of the Study:
- To develop an accessible R Shiny App called GNOSIS (GeNomics explOrer using StatistIcal and Survival analysis in R).
- To enable efficient exploration and visualization of clinical and genomic cancer data for researchers.
Main Methods:
- Developed GNOSIS as an R Shiny App utilizing various R packages.
- Integrated functionalities for data upload, exploration, recoding, subsetting, visualization, statistical analysis, mutation analysis, and survival analysis.
- Ensured reproducible research through downloadable input logs and R scripts.
Main Results:
- GNOSIS provides an intuitive graphical user interface for complex data exploration.
- The app facilitates the identification of prognostic markers through specialized analysis modules, particularly survival analysis.
- Supports clinician-researchers in enhancing their statistical computing skills.
Conclusions:
- GNOSIS offers a user-friendly platform for exploring cancer genomics data.
- The tool democratizes the identification of genomic prognostic markers.
- Facilitates reproducible research and skill development for researchers in the field.
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