gEAR: gene Expression Analysis Resource portal for community-driven, multi-omic data exploration

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.

Greater epithelial ridge cells are the principal organoid-forming progenitors of the mouse cochlea

“…Of course, the differences between technologies used in the different studies come with distinct limitations, such as the numbers of genes associated with individual cells that could affect clustering outcomes. Integration into the gEAR data depository ( Orvis et al, 2020 ) provides an instrument for directly comparing the datasets. We found that cell density is an important variable for activating GER cell growth, and that direct cell contact is essential.…”

“…The RNA sequencing data generated in this paper is available from GEO with accession number GSE162308. The data are also available at gEAR, a gene Expression Analysis Resource ( Orvis et al, 2020 ), via PERMA-LINK https://umgear.org//index.html?layout_id=afd2eb77&gene_symbol_exact_match=1 . In gEAR, it is possible to project each gene’s expression value into the tSNE plot shown in Figure 3A , into a cochlear illustration with all cell types identified (based on Figures 2A – 2C ), as well as violin plots concordant with Table S3 .…”

Expression bias in retinoic acid responsive genes defines variations in neural differentiation of human pluripotent stem cells

“…In striking contrast, low PC1 maps to the pluripotent epiblast and emerging neural lineages (Figure 6E, in purple to pink and Figure S7B-D) with high expression of SOX3, LHX2, PAX6, EMX2, FEZF2, and RAX . The expression patterns of these and other genes can be explored at nemoanalytics.org/p?l=KimEtAL2021&g=FEZF2 , where we have used the gEAR and NeMO Analytics framework (Orvis et al, 2020) to construct an integrated gene expression data environment spanning the collection of in vivo and in vitro data examined in this study.…”

Transcriptomic characterization of dying hair cells in the avian cochlea

“…The RNA sequencing data generated in this paper is stored in two SingleCellExperiment containers that are provided as Data S1 and S2. The data are also available at gEAR, a gene Expression Analysis Resource (https://umgear.org/) (Orvis et al, 2020)…”