Cell Ontology
This repository contains the source for the Cell Ontology. Most users do not need to edit content in this repo directly. However we are happy to train new editors.
Request changes to the ontology
We welcome edit requests from anyone - especially if you plan to use the Cell Ontology for annotation. To request a new term, please use our new term request template. For any other requests please choose one of our other templates), or open a blank ticket. If you wish to request a set of related terms, you may link a MIRACL sheet (Lubiana et al., 2022) to a ticket containing a general description of the requested set of terms.
Browse the ontology using OLS
https://www.ebi.ac.uk/ols4/ontologies/cl
Latest CL release files
https://github.com/obophenotype/cell-ontology/releases/latest
Description of release files
https://oboacademy.github.io/obook/reference/release-artefacts/
For more details on CL see:
Editors documentation:
- CL Editor doc
- Generic ODK workflows
- OBO Academy oBook - General ontology editor and developer documentation and tutorials.
Training materials from the 2020 CL Training Workshop are available at https://github.com/obophenotype/cell-ontology-training.
Twice monthly calls
Third Wednesday of month, 8am PT/11am ET (CL)
Third Monday of month, 8am PT/11am ET (Uberon)
Agenda here.
Cite
Diehl,A.D., Meehan,T.F., Bradford,Y.M., Brush,M.H., Dahdul,W.M., Dougall,D.S., He,Y., Osumi-Sutherland,D., Ruttenberg,A., Sarntivijai,S., et al. (2016) The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability. J. Biomed. Semantics, 7, 44.
GitHub Actions Triggers
To trigger an automated human readable diff, add the following tag to a comment in your pull request: #gogoeditdiff
Applications
CL is used in a number of applications including:
CellxGene
The Cell ontology is used to annotate cell types on the single cell transcriptomics platform CellxGene. All datasets on CellXGene are annotated according to a standard schema that specifies the use of CL to record Cell Type. Uses in CellXgene tools:
- In the Discover tool, the structure of CL is used to drive faceted searching for datasets and collections by Cell Type.
- In the Gene Expression, CL annotation is used to aggregate expression data.
- In CellGuide CL provides content and CL term names and synonyms drive search and graphical browsing.
- The Cell Census API supports retrieval of cross-dataset matrices containing transcriptmics data for cells annotated with specified terms from CL and other ontologies.
HuBMAP
HuBMAP develops tools to create an open, global atlas of the human body at the cellular level. The Cell Ontology is used in annotating cell types in the tools developed.
HuBMAP Consortium (2019) The human body at cellular resolution: the NIH Human Biomolecular Atlas Program. Nature, 574, 187–192
Human Cell Atlas (HCA)
The Human Cell Atlas (HCA) is an international group of researchers using a combination of these new technologies to create cellular reference maps. The HCA use CL to annotated cells in their reference maps.
Regev,A., Teichmann,S.A., Lander,E.S., Amit,I., Benoist,C., Birney,E., Bodenmiller,B., Campbell,P., Carninci,P., Clatworthy,M., et al. (2017) The Human Cell Atlas. Elife, 6.
Single Cell Expression Atlas
The EBI single cell expression atlas is an extension to EBI expression atlas that displays gene expression in single cells. Cell types in the single cell expression atlas linked with terms from the Cell Ontology.
Papatheodorou,I., Moreno,P., Manning,J., Fuentes,A.M.-P., George,N., Fexova,S., Fonseca,N.A., Füllgrabe,A., Green,M., Huang,N., et al. (2020) Expression Atlas update: from tissues to single cells. Nucleic Acids Res., 48, D77–D83.
BRAIN Initiative Cell Census Network (BICCN)/Brain Data Standards Ontology
The BICCN created a high-resolution atlas of cell types in the primary motor based on single cell transcriptomics. These cell types are represented in the brain data standards ontology which anchors to cell types in the cell ontology.
Tan, S.Z.K., Kir, H., Aevermann, B.D. et al. Brain Data Standards - A method for building data-driven cell-type ontologies. Sci Data 10, 50 (2023). https://doi.org/10.1038/s41597-022-01886-2
ENCODE
The National Human Genome Research Institute (NHGRI) launched a public research consortium named ENCODE, the Encyclopedia Of DNA Elements, in September 2003, to carry out a project to identify all functional elements in the human genome sequence. The ENCODE DCC uses Uberon to annotate samples
Malladi, V. S., Erickson, D. T., Podduturi, N. R., Rowe, L. D., Chan, E. T., Davidson, J. M., … Hong, E. L. (2015). Ontology application and use at the ENCODE DCC. Database : The Journal of Biological Databases and Curation, 2015, bav010–. doi:10.1093/database/bav010
FANTOMS
FANTOM5 is using Uberon and CL to annotate samples allowing for transcriptome analyses with cell-type and tissue-level specificity.
Lizio, M., Harshbarger, J., Shimoji, H., Severin, J., Kasukawa, T., Sahin, S., … Kawaji, H. (2015). Gateways to the FANTOM5 promoter level mammalian expression atlas. Genome Biology, 16(1),
LINCS
Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High-Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS) http://jbx.sagepub.com/content/early/2014/02/11/1087057114522514.full