Nature MethodsBioinformaticsPeer-reviewed journal article
gEAR: gene Expression Analysis Resource portal for community-driven, multi-omic data exploration
Joshua OrvisiD, Brian Gottfried, Jayaram KancherlaiD, Ricky S. AdkinsiD, Yang SongiD, Amiel A. DroriD, Dustin OlleyiD, Kevin P. RoseiD, Elena Chrysostomou, Michael C. KellyiD, Beatrice C. MiloniD, Maggie S. MaterniD, Héla AzaieziD, Brian R. HerbiD, Carlo ColantuoniiD, Robert L. CarteriD, Seth A. AmentiD, Matthew W. KelleyiD, Owen R. WhiteiD, Héctor Corrada BravoiD, Anup MahurkariD, Ronna P. HertzanoiD
Abstract
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.
- organism: human
- organism: mouse
- organism: multiple species
- assay: bulk RNA-seq
- assay: scRNA-seq
- assay: spatial transcriptomics
- assay: DNA methylation
- research focus: database / resource
- research focus: dimensionality reduction
- research focus: clustering
- research focus: cell type annotation
- approach: statistical model
- approach: benchmark study
- Citations
- 214
- FWCI
- 11.21
- Field percentile
- top 1%
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