Common cell type nomenclature for the mammalian brain

Author:

Miller Jeremy A1ORCID,Gouwens Nathan W1ORCID,Tasic Bosiljka1ORCID,Collman Forrest1ORCID,van Velthoven Cindy TJ1ORCID,Bakken Trygve E1ORCID,Hawrylycz Michael J1ORCID,Zeng Hongkui1ORCID,Lein Ed S1ORCID,Bernard Amy1ORCID

Affiliation:

1. Allen Institute, Seattle, United States

Abstract

The advancement of single-cell RNA-sequencing technologies has led to an explosion of cell type definitions across multiple organs and organisms. While standards for data and metadata intake are arising, organization of cell types has largely been left to individual investigators, resulting in widely varying nomenclature and limited alignment between taxonomies. To facilitate cross-dataset comparison, the Allen Institute created the common cell type nomenclature (CCN) for matching and tracking cell types across studies that is qualitatively similar to gene transcript management across different genome builds. The CCN can be readily applied to new or established taxonomies and was applied herein to diverse cell type datasets derived from multiple quantifiable modalities. The CCN facilitates assigning accurate yet flexible cell type names in the mammalian cortex as a step toward community-wide efforts to organize multi-source, data-driven information related to cell type taxonomies from any organism.

Funder

Allen Institute

National Institute of Mental Health

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference71 articles.

1. A multimodal cell census and atlas of the mammalian primary motor cortex;Adkins,2020

2. Neuro-symbolic representation learning on biological knowledge graphs;Alshahrani;Bioinformatics,2017

3. Towards the automatic classification of neurons;Armañanzas;Trends in Neurosciences,2015

4. Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse;Bakken,2020

5. Single-cell RNA-seq uncovers shared and distinct axes of variation in dorsal LGN neurons in mice, non-human primates and humans;Bakken,2020

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