A guide to the BRAIN initiative cell census network data ecosystem

Hawrylycz, M.; Martone, M.E.; Ascoli, G.A.; Bjaalie, J.G.; Dong, H.W.; Ghosh, S.S.; ... ; Zingg, B. (2023)

Article / Letter to editor

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.

• All authors: Hawrylycz, M.; Martone, M.E.; Ascoli, G.A.; Bjaalie, J.G.; Dong, H.W.; Ghosh, S.S.; Gillis, J.; Hertzano, R.; Haynor, D.R.; Hof, P.R.; Kim, Y.; Lein, E.; Liu, Y.F.; Miller, J.A.; Mitra, P.P.; Mukamel, E.; Ng, L.; Osumi-Sutherland, D.; Peng, H.C.; Ray, P.L.; Sanchez, R.; Regev, A.; Ropelewski, A.; Scheuermann, R.H.; Tan, S.Z.K.; Thompson, C.L.; Tickle, T.; Tilgner, H.; Varghese, M.; Wester, B.; White, O.; Zeng, H.K.; Aevermann, B.; Allemang, D.; Ament, S.; Athey, T.L.; Baker, C.; Baker, K.S.; Baker, P.M.; Bandrowski, A.; Banerjee, S.; Bishwakarma, P.; Carr, A.; Chen, M.; Choudhury, R.; Cool, J.; Creasy, H.; D'Orazi, F.; Degatano, K.; Dichter, B.; Ding, S.L.; Dolbeare, T.; Ecker, J.R.; Fang, R.X.; Fillion-Robin, J.C.; Fliss, T.P.; Gee, J.; Gillespie, T.; Gouwens, N.; Zhang, G.Q.; Halchenko, Y.O.; Harris, N.L.; Herb, B.R.; Hintiryan, H.; Hood, G.; Horvath, S.; Huo, B.X.; Jarecka, D.; Jiang, S.D.; Khajouei, F.; Kiernan, E.A.; Kir, H.; Kruse, L.; Lee, C.K.Y.; Lelieveldt, B.; Li, Y.; Liu, H.Q.; Liu, L.J.; Markuhar, A.; Mathews, J.; Mathews, K.L.; Mezias, C.; Miller, M.I.; Mollenkopf, T.; Mufti, S.; Mungall, C.J.; Orvis, J.; Puchades, M.A.; Qu, L.; Receveur, J.P.; Ren, B.; Sjoquist, N.; Staats, B.; Tward, D.; Velthoven, C.T.J. van; Wang, Q.X.; Xie, F.M.; Xu, H.; Yao, Z.Z.; Yun, Z.X.; Zhang, Y.R.; Zheng, W.J.; Zingg, B.
• Date: 2023-06-01
• Journal: PLoS Biology
• Volume: 21
• Issue: 6
• DOI: doi:10.1371/journal.pbio.3002133
• Sponsorship: Horizon 2020 (H2020)
• Grant number: R01 NS096720