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GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal
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 explOre...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9051584/ https://www.ncbi.nlm.nih.gov/pubmed/35677713 http://dx.doi.org/10.12688/hrbopenres.13476.2 |
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author | King, Lydia Flaus, Andrew Coughlan, Simone Holian, Emma Golden, Aaron |
author_facet | King, Lydia Flaus, Andrew Coughlan, Simone Holian, Emma Golden, Aaron |
author_sort | King, Lydia |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9051584 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-90515842022-06-07 GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal King, Lydia Flaus, Andrew Coughlan, Simone Holian, Emma Golden, Aaron HRB Open Res Software Tool Article 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. F1000 Research Limited 2022-09-12 /pmc/articles/PMC9051584/ /pubmed/35677713 http://dx.doi.org/10.12688/hrbopenres.13476.2 Text en Copyright: © 2022 King L et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Tool Article King, Lydia Flaus, Andrew Coughlan, Simone Holian, Emma Golden, Aaron GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal |
title | GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal |
title_full | GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal |
title_fullStr | GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal |
title_full_unstemmed | GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal |
title_short | GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal |
title_sort | gnosis: an r shiny app supporting cancer genomics survival analysis with cbioportal |
topic | Software Tool Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9051584/ https://www.ncbi.nlm.nih.gov/pubmed/35677713 http://dx.doi.org/10.12688/hrbopenres.13476.2 |
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