# A Community Framework for Data-driven Brain Transcriptomic Cell Type Definition, Ontology, and Nomenclature

> **NIH NIH RF1** · ALLEN INSTITUTE · 2020 · $2,770,416

## Abstract

Project Summary: A Data-driven Framework for Brain Transcriptomic Cell Type Definition, Ontology, and
Nomenclature
Defining the complete census of neuronal and non-neuronal cell types in the brain is a major priority for the NIH BRAIN
Initiative, since cellular complexity is a major barrier to understanding brain function and the mechanistic underpinnings
of disease. Single cell transcriptomics has revolutionized this field with the scale and information content to
characterize complex tissues, and is leading quickly to a brain-wide classification of cell types in mouse, monkey and
human. Transcriptomics is also uniquely suited to allow quantitative comparisons across species, across developmental
time, and between brain and other organs, and is the common denominator with other large-scale efforts to
characterize the entire human body in the Human Cell Atlas and HuBMAP consortia. The opportunity is now here to
create a new quantitative framework for defining cell types in the brain, generating a new data-driven cell type ontology
and a nomenclature convention similar in concept to the reference genomes that unify genomics. Importantly, the
design principles should be extensible beyond brain to other organs so that the schema can be adopted across the other
major consortium projects, but also to incorporate other important cellular phenotypes important for neurobiological
function. The proposed project aims to bring together a team of experts in single-cell transcriptomics, informatics,
ontology development and computational biology who are also leaders and members of the major cell type consortia to
develop a data-driven framework of brain cell types. First, the project aims to develop standards for quantitative
definitions of transcriptomic-based cell types from the BRAIN Initiative Cell Census Network (BICCN) datasets, and tools
for mapping other datasets (other data types or data from other researchers) to this reference. This will create
reference data structures for features of transcriptomic cell types and taxonomies that will be deployed through the
BICCN portal. Secondly, the project aims to build on prior work on developing cell and phenotype ontologies to develop
a new, data-driven formal cell ontology for the whole brain reference. Part of this ontology is a nomenclature
convention for systematic naming of cell types that allows similar naming of homologous cell types across species.
Finally, a major goal is to engage the international cell type community in developing and refining these standards and
reference classification to ensure their usefulness and widespread adoption. This will involve active engagement of the
community through a working group structure, and periodic domain expert workshops with the BICCN, HCA, HuBMAP
and INCF consortia. All standards, ontologies and tools will be deployed on the BICCN portal with mechanisms for
community feedback and vetting.

## Key facts

- **NIH application ID:** 10012886
- **Project number:** 1RF1MH123220-01
- **Recipient organization:** ALLEN INSTITUTE
- **Principal Investigator:** Michael Hawrylycz
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $2,770,416
- **Award type:** 1
- **Project period:** 2020-09-04 → 2023-09-03

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10012886

## Citation

> US National Institutes of Health, RePORTER application 10012886, A Community Framework for Data-driven Brain Transcriptomic Cell Type Definition, Ontology, and Nomenclature (1RF1MH123220-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10012886. Licensed CC0.

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