Litcius/Paper detail

GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal

Lydia King, Andrew Flaus, Simone Coughlan, Emma Holian, Aaron Golden

2022HRB Open Research25 citationsDOIOpen Access PDF

Abstract

Exploratory analysis of cancer consortia data curated by the cBioPortal repository typically requires advanced programming skills and expertise to identify novel genomic prognostic markers that have the potential for both diagnostic and therapeutic exploitation. We developed GNOSIS (GeNomics explOrer using StatistIcal and Survival analysis in R), an R Shiny App incorporating a range of R packages enabling users to efficiently explore and visualise such clinical and genomic data. GNOSIS provides an intuitive graphical user interface and 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. GNOSIS also facilitates reproducible research by providing downloadable input logs and R scripts from each session, and so offers an excellent means of supporting clinician-researchers in developing their statistical computing skills.

Topics & Concepts

UploadScripting languageComputer scienceSession (web analytics)DownloadGenomicsStatistical analysisInterface (matter)Exploratory data analysisExploratory analysisData scienceWorld Wide WebGenomeData miningBiologyOperating systemGeneticsStatisticsMathematicsBubbleMaximum bubble pressure methodGeneBioinformatics and Genomic NetworksGene expression and cancer classificationGenetic Associations and Epidemiology