RT Journal Article
SR Electronic
T1 gEAR: gene Expression Analysis Resource portal for community-driven, multi-omic data exploration
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.08.28.272039
DO 10.1101/2020.08.28.272039
A1 Joshua Orvis
A1 Brian Gottfried
A1 Jayaram Kancherla
A1 Ricky S. Adkins
A1 Yang Song
A1 Amiel A. Dror
A1 Dustin Olley
A1 Kevin Rose
A1 Elena Chrysostomou
A1 Michael C. Kelly
A1 Beatrice Milon
A1 Maggie S. Matern
A1 Hela Azaiez
A1 Brian Herb
A1 Carlo Colantuoni
A1 Robert L. Carter
A1 Seth A. Ament
A1 Matthew W. Kelley
A1 Owen White
A1 Hector Corrada Bravo
A1 Anup Mahurkar
A1 Ronna Hertzano
YR 2020
UL http://biorxiv.org/content/early/2020/08/31/2020.08.28.272039.abstract
AB The gEAR portal (gene Expression Analysis Resource, umgear.org) is an open access community-driven tool for multi-omic and multi-species data visualization, analysis and sharing. The gEAR supports visualization of multiple RNA-seq data types (bulk, sorted, single cell/nucleus) and epigenomics data, from multiple species, time points and tissues in a single-page, user-friendly browsable format. An integrated scRNA-seq workbench provides access to raw data of scRNA-seq datasets for de novo analysis, as well as marker-gene and cluster comparisons of pre-assigned clusters. Users can upload, view, analyze and privately share their own data in the context of previously published datasets. Short, permanent URLs can be generated for dissemination of individual or collections of datasets in published manuscripts. While the gEAR is currently curated for auditory research with over 90 high-value datasets organized in thematic profiles, the gEAR also supports the BRAIN initiative (via nemoanalytics.org) and is easily adaptable for other research domains.Competing Interest StatementThe authors have declared no competing interest.