1 Introduction

Exploratory, statistical and survival analysis of cancer genomic data is extremely important and can lead to new discoveries, such as the identification of novel genomic prognostic markers, that have the potential to advance our understanding of cancer and ultimately benefit patients. These analyses are often performed on data available from a number of consortia websites, such as cBio Cancer Genomics Portal (cBioPortal), which is one of the best known and commonly used consolidated curations that hosts data from large consortium efforts. While cBioPortal provides both graphical user interface (GUI)-based and representational state transfer mediated means for researchers to explore and analyse clinical and genomics data, its capabilities have their limitations and oftentimes, to explore specific hypotheses, users need to perform a more sophisticated ‘off site’ analysis that typically requires users to have some prior programming experience.

To overcome these limitations and provide a GUI that facilitates the visualisation and interrogation of cancer genomics data, particularly cBioPortal-hosted data, using standard biostatistical methodologies, we developed an R Shiny app called GeNomics explOrer using StatistIcal and Survival analysis in R (GNOSIS). GNOSIS was initially developed as part of our study, using the METABRIC data, to investigate whether survival outcomes are associated with genomic instability in luminal breast cancers and was further developed to enable the exploration, analysis and incorporation of a diverse range of genomic features with clinical data in a research or clinical setting.

GNOSIS leverages a number of R packages and provides an intuitive GUI with multiple tab panels supporting a range of functionalities, including data upload and initial exploration, data recoding and subsetting, data visualisations, statistical analysis, mutation analysis and, in particular, survival analysis to identify prognostic markers. In addition, GNOSIS also helps researchers carry out reproducible research by providing downloadable input logs (Shiny_Log.txt) from each session.

GNOSIS has been submitted to Bioconductor to aid researchers in carrying out a reproducable, comprehensive statistical and survival analysis using data obtained from cBioPortal, or otherwise.

2 Installation

if (!requireNamespace("BiocManager", quietly = TRUE)) {


3 Loading the package


4 Launching GNOSIS


5 GNOSIS layout

The GNOSIS GUI has 4 main elements: (1) A sidebar where each analysis tab can be selected, the Exploratory Tables tab is selected and displayed. (2) Tab panels within each tab, allowing multiple operations to be carried out and viewed in the one tab. (3) A box sidebar allowing users to select inputs, alter arguments and customise and export visualisations. (4) Main viewing panel displaying output.

6 Data upload and preview

Users can upload their own clinical, CNA or mutation data stored on their local machine, or select a cBioPortal study to upload:

A preview of the uploaded/selected data is provided in the GNOSIS viewing panel to ensure that the data has been read in correctly: