Title: ScanGEO: parallel mining of high-throughput gene expression data.
Authors: Koeppen, Katja; Stanton, Bruce A; Hampton, Thomas H
Published In Bioinformatics, (2017 Nov 01)
Abstract: 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.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.firstname.lastname@example.org.Supplementary data are available at Bioinformatics online.
PubMed ID: 29036513
MeSH Terms: Data Mining; Gene Expression Profiling/methods*; Humans; Software*