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Article type: Research Article
Authors: Noori, Ayusha; 1 | Jayakumar, Rojashreea; 1 | Moturi, Vaishnavia; 1 | Li, Zhaozhib | Liu, Rongxina | Serrano-Pozo, Albertoa; c | Hyman, Bradley T.a; c | Das, Sudeshnaa; c; *
Affiliations: [a] Department of Neurology, Massachusetts General Hospital, Boston, MA, USA | [b] Department of Computational Biology, Cornell University, Ithaca, NY, USA | [c] Harvard Medical School, Boston, MA, USA
Correspondence: [*] Correspondence to: Sudeshna Das, PhD, MIND Data Science Lab, 65 Landsdowne St., Cambridge, MA 02139, USA. Tel.: +1 617 768 8254; Fax: +1 617 213 5418; E-mail: [email protected].
Note: [1] These authors contributed equally to this work.
Abstract: Background:Recent Alzheimer’s disease (AD) discoveries are increasingly based on studies from a variety of omics technologies on large cohorts. Currently, there is no easily accessible resource for neuroscientists to browse, query, and visualize these complex datasets in a harmonized manner. Objective:Create an online portal of public omics datasets for AD research. Methods:We developed Alzheimer DataLENS, a web-based portal, using the R Shiny platform to query and visualize publicly available transcriptomics and genetics studies of AD on human cohorts. To ensure consistent representation of AD findings, all datasets were processed through a uniform bioinformatics pipeline. Results:Alzheimer DataLENS currently houses 2 single-nucleus RNA sequencing datasets, over 30 bulk RNA sequencing datasets from 19 brain regions and 3 cohorts, and 2 genome-wide association studies (GWAS). Available visualizations for single-nucleus data include bubble plots, heatmaps, and UMAP plots; for bulk expression data include box plots and heatmaps; for pathways include protein-protein interaction network plots; and for GWAS results include Manhattan plots. Alzheimer DataLENS also links to two other knowledge resources: the AD Progression Atlas and the Astrocyte Atlas. Conclusions:Alzheimer DataLENS is a valuable resource for investigators to quickly and systematically explore omics datasets and is freely accessible at https://alzdatalens.partners.org.
Keywords: Alzheimer’s disease, database, genetics, multiomics, single-cell RNA-seq, transcriptomics
DOI: 10.3233/JAD-230884
Journal: Journal of Alzheimer's Disease, vol. Pre-press, no. Pre-press, pp. 1-11, 2024
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