Garnett
Garnett annotates cell types in single-cell transcriptional profiling and single-cell chromatin accessibility datasets using an interpretable hierarchical markup language that specifies cell type-specific genes.
Key Features:
- Rapid Annotation: Automates cell type annotation to accelerate a process that is traditionally manual and time-consuming.
- Hierarchical Markup Language: Employs an interpretable hierarchical markup language to define cell type-specific gene markers and hierarchical relationships among cell types.
- Data Modality Support: Classifies cells in both single-cell transcriptional profiling and single-cell chromatin accessibility datasets.
- Cross-Dataset Compatibility: Performs classification across diverse datasets derived from tissue samples and whole organisms.
- Cross-Species Application: Supports the classification of cell types across different species.
Scientific Applications:
- Single-cell genomics: Annotating cell types in single-cell transcriptional and chromatin accessibility studies to enable interpretation of cellular composition and heterogeneity.
- Comparative cell type mapping: Enabling cross-dataset and cross-species mapping of cell types across tissue samples and whole organisms.
- Cellular heterogeneity and process analysis: Facilitating investigation of complex biological processes at the cellular level through annotated single-cell profiles.
Methodology:
Garnett uses an interpretable hierarchical markup language to specify cell type-specific genes and classify cells in single-cell transcriptional and chromatin accessibility datasets.
Topics
Details
- Tool Type:
- library
- Programming Languages:
- R
- Added:
- 11/14/2019
- Last Updated:
- 12/2/2020
Operations
Publications
Pliner HA, Shendure J, Trapnell C. Supervised classification enables rapid annotation of cell atlases. Nature Methods. 2019;16(10):983-986. doi:10.1038/s41592-019-0535-3. PMID:31501545. PMCID:PMC6791524.
PMID: 31501545
PMCID: PMC6791524
Funding: - U.S. Department of Health & Human Services | National Institutes of Health: DP1HG007811, DP2HD088158, R01HG006283, R01HL118342, RC2DK114777, U54DK107979
- National Science Foundation: DGE-1256082