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The Neuroscience Multi-Omic Archive: a BRAIN Initiative resource for single-cell transcriptomic and epigenomic data from the mammalian brain

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NUCLEIC ACIDS RESEARCH
卷 51, 期 D1, 页码 D1075-D1085

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OXFORD UNIV PRESS
DOI: 10.1093/nar/gkac962

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Scalable technologies for single-cell transcriptome and epigenome sequencing are revolutionizing our understanding of cell types and states. The BICCN, part of the BRAIN Initiative, is utilizing these technologies on an unprecedented scale to map cell types in the mammalian brain. To enhance data accessibility, the NIH has established the NeMO Archive as the primary repository for genomics data from the BRAIN Initiative, containing transcriptomic and epigenomic data from over 50 million brain cells.
Scalable technologies to sequence the transcriptomes and epigenomes of single cells are transforming our understanding of cell types and cell states. The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative Cell Census Network (BICCN) is applying these technologies at unprecedented scale to map the cell types in the mammalian brain. In an effort to increase data FAIRness (Findable, Accessible, Interoperable, Reusable), the NIH has established repositories to make data generated by the BICCN and related BRAIN Initiative projects accessible to the broader research community. Here, we describe the Neuroscience Multi-Omic Archive (NeMO Archive; nemoarchive.org), which serves as the primary repository for genomics data from the BRAIN Initiative. Working closely with other BRAIN Initiative researchers, we have organized these data into a continually expanding, curated repository, which contains transcriptomic and epigenomic data from over 50 million brain cells, including single-cell genomic data from all of the major regions of the adult and prenatal human and mouse brains, as well as substantial single-cell genomic data from non-human primates. We make available several tools for accessing these data, including a searchable web portal, a cloud-computing interface for large-scale data processing (implemented on Terra, terra.bio), and a visualization and analysis platform, NeMO Analytics (nemoanalytics.org).

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