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ScanGEO: parallel mining of high-throughput gene expression data.
Koeppen, Katja; Stanton, Bruce A; Hampton, Thomas H.
Afiliación
  • Koeppen K; Department of Microbiology and Immunology, The Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.
  • Stanton BA; Department of Microbiology and Immunology, The Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.
  • Hampton TH; Department of Microbiology and Immunology, The Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.
Bioinformatics ; 33(21): 3500-3501, 2017 Nov 01.
Article en En | MEDLINE | ID: mdl-29036513
ABSTRACT

SUMMARY:

Current options to mine publicly available gene expression data deposited in NCBI's gene expression omnibus (GEO), such as the GEO web portal and related applications, are optimized to reanalyze a single study, or search for a single gene, and therefore require manual intervention to reanalyze multiple studies for user-specified gene sets. ScanGEO is a simple, user-friendly Shiny web application designed to identify differentially expressed genes across all GEO studies matching user-specified criteria, for a flexible set of genes, visualize results and provide summary statistics and other reports using a single command. AVAILABILITY AND IMPLEMENTATION The ScanGEO source code is written in R and implemented as a Shiny app that can be freely accessed at http//scangeo.dartmouth.edu/ScanGEO/. For users who would like to run a local instantiation of the app, the R source code is available under a GNU GPLv3 license at https//github.com/StantonLabDartmouth/AppScanGEO. CONTACT katja.koeppen@dartmouth.edu. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Perfilación de la Expresión Génica Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Perfilación de la Expresión Génica Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos