bioRxivBioinformaticsPreprint
The BRAIN Initiative Cell Census Data Ecosystem: A User's Guide
Michael HawrylycziD, Maryann Elizabeth MartoneiD, Patrick R. HofiD, Ed S. LeiniD, Aviv RegeviD, Giorgio A. AscoliiD, Jan Gunnar BjaalieiD, Hong‐Wei DongiD, Satrajit GhoshiD, Jesse A GillisiD, Ronna P. HertzanoiD, David R. HaynoriD, Yongsoo KimiD, Yufeng LiuiD, Jeremy A. MilleriD, Partha P. MitraiD, Eran A. MukameliD, David Osumi-SutherlandiD, Hanchuan PengiD, Patrick L. RayiD, Raymond E.A. SancheziD, Alexander J. RopelewskiiD, Richard H. ScheuermanniD, Shawn Zheng Kai TaniD, Timothy L. TickleiD, , Brian ZinggiD
Abstract
Characterizing cellular diversity at different levels of biological organization across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also required to manipulate cell types in controlled ways, and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data generating centers, data archives and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain and demonstration of prototypes for human and non-human primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed, and to accessing and using the BICCN data and its extensive resources, including the BRAIN Cell Data Center (BCDC) which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted by the BICCN toward FAIR (Wilkinson et al. 2016a) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.
- organism: mouse
- organism: human
- organism: non-human primate
- assay: spatial transcriptomics
- assay: bulk RNA-seq
- research focus: database / resource
- research focus: benchmarking
- research focus: cell type annotation
- approach: benchmark study
- Citations
- 7
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