American Journal of Respiratory Cell and Molecular BiologySystems BiologyPeer-reviewed journal article
LungMAP Portal Ecosystem: Systems-Level Exploration of the Lung
Nathan GaddisiD, Joshua D. FortriedeiD, Minzhe GuoiD, Eric E. BardesiD, Michal KouriliD, Scott Tabar, Kevin A. BurnsiD, Mary-Anne ArdiniiD, Stephanie Loos, Daniel Schnell, Kang JiniD, Balaji IyeriD, Yina DuiD, Bing‐Xing HuoiD, Anukana BhattacharjeeiD, Jeff Korte, Ruchi Munshi, Victoria Smith, Andrew Herbst, Joseph A. KitzmilleriD, Gérémy ClairiD, James P. CarsoniD, Joshua AdkinsiD, Edward E. MorriseyiD, Gloria PryhuberiD, , Nathan SalomonisiD
Abstract
An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a gateway portal. This portal connects a broad-spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease and drug treatment. These atlases are provided as independent and integrated queriable datasets, with an emphasis on dynamic visualization, figure generation and reference-based classification of user-provided datasets (Azimuth). As this resource grows, we intend to increase the breadth of available interactive interfaces, data portals and datasets from LungMAP and external research efforts.
- organism: human
- organism: mouse
- organism: rat
- assay: bulk RNA-seq
- assay: scRNA-seq
- assay: imaging
- research focus: database / resource
- approach: statistical model
- Citations
- 62
- FWCI
- 3.43
- Field percentile
- top 5%
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