ScanGEO: parallel mining of high-throughput gene expression data.
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.
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