A guide to the BRAIN Initiative Cell Census Network data ecosystem
Michael Hawrylycz, Maryann E. Martone, Giorgio A. Ascoli, Jan G. Bjaalie, Hong‐Wei Dong, Satrajit Ghosh, Jesse Gillis, Ronna Hertzano, David R. Haynor, Patrick R. Hof, Yongsoo Kim, Ed S. Lein, Yufeng Liu, Jeremy A. Miller, Partha P. Mitra, Eran A. Mukamel, Lydia Ng, David Osumi-Sutherland, Hanchuan Peng, Patrick L. Ray, Raymond Sanchez, Aviv Regev, Alex Ropelewski, Richard H. Scheuermann, Shawn Zheng Kai Tan, Carol L. Thompson, Timothy L. Tickle, Hagen Tilgner, Merina Varghese, Brock A. Wester, Owen White, Hongkui Zeng, Brian D. Aevermann, David Allemang, Seth A. Ament, Thomas L. Athey, C L Baker, Katherine Baker, Pamela Baker, Anita Bandrowski, Samik Banerjee, Prajal Bishwakarma, Ambrose Carr, Min Chen, Roni Choudhury, Jonah Cool, Heather H. Creasy, Florence D. D’Orazi, Kylee Degatano, Ben Dichter, Song‐Lin Ding, Tim Dolbeare, Joseph R. Ecker, Rongxin Fang, Jean‐Christophe Fillion‐Robin, Timothy P. Fliss, James C. Gee, Tom Gillespie, Nathan W. Gouwens, Guo‐Qiang Zhang, Yaroslav O. Halchenko, Nomi L. Harris, Brian R. Herb, Houri Hintiryan, Gregory Hood, S. Horvath, Bing‐Xing Huo, Dorota Jarecka, Shengdian Jiang, Farzaneh Khajouei, Elizabeth Kiernan, Hüseyin Kır, Lauren Kruse, Changkyu Lee, Boudewijn P. F. Lelieveldt, Yang Eric Li, Hanqing Liu, Lijuan Liu, Anup Markuhar, James C. Mathews, Kaylee L. Mathews, Christopher Mezias, Michael I. Miller, Tyler Mollenkopf, Shoaib Mufti, Chris Mungall, Joshua Orvis, Maja Puchades, Lei Qu, Joseph P. Receveur, Bing Ren, Nathan Sjoquist, Brian Staats, Daniel J. Tward, Cindy T. J. van Velthoven, Quanxin Wang, Fangming Xie, Hua Xu, Zizhen Yao, Zhixi Yun
Abstract
Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential 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 with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and 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 toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.