celltypeEnrich: a consensus-based scRNA-seq cluster annotation tool
- 1Iowa State University
Abstract
Motivation Single-cell RNA sequencing (scRNA-seq) cluster annotation is a critical step in data analysis. Current methods are time-consuming, difficult to reproduce, or limited in tissue or species coverage. Results We developed celltypeEnrich, a cluster-level annotation tool that uses a hypergeometric test to identify enrichment of cell-type-specific genes from input gene lists. Enrichment results from up to 26 reference datasets are used to determine a consensus annotation. Benchmarking using scRNA-seq datasets from three tissues spanning two species showed 62-72% annotation accuracy for celltypeEnrich, generally outperforming other tools, which had either lower accuracy, incomplete tissue coverage, or the need for parameter optimization. The performance of celltypeEnrich remained stable when input gene lists were down-sampled to 25% of their original size. Availability and Implementation celltypeEnrich is freely available at (https://celltypeenrich.gdcb.iastate.edu) as an R Shiny web application under the MIT license for non-profit academic use.
Related
- CHACAM: a cell-cell interaction-guided hierarchical attention model for high-precision cell identity annotation of scRNA-seq data in early C. elegans embryogenesis
- Cell-type separability predicts annotation accuracy and outweighs algorithm choice: a factorial benchmark across seven scRNA paradigms
- GOlien tool: fast and scalable GO term annotation of proteins using a Shannon-entropy k-mer model
- Genome annotation of a cluster FD Arthrobacter bacteriophage Casab isolated from soil in Tennessee.
- A semi-automated tool for improving Assessments and Lab Tests data annotation in ImmPort
BibTeX
@misc{rutledge2026celltypeenrich,
title = {{celltypeEnrich: a consensus-based scRNA-seq cluster annotation tool}},
author = {S. Rutledge and G. Tuteja},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.15.751735},
url = {https://www.biorxiv.org/content/10.64898/2026.09.15.751735v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - celltypeEnrich: a consensus-based scRNA-seq cluster annotation tool
AU - S. Rutledge
AU - G. Tuteja
PY - 2026
DA - 2026/09/15
PB - bioRxiv
DO - 10.64898/2026.09.15.751735
UR - https://www.biorxiv.org/content/10.64898/2026.09.15.751735v1
AB - Motivation Single-cell RNA sequencing (scRNA-seq) cluster annotation is a critical step in data analysis. Current methods are time-consuming, difficult to reproduce, or limited in tissue or species coverage. Results We developed celltypeEnrich, a cluster-level annotation tool that uses a hypergeometric test to identify enrichment of cell-type-specific genes from input gene lists. Enrichment results from up to 26 reference datasets are used to determine a consensus annotation. Benchmarking using scRNA-seq datasets from three tissues spanning two species showed 62-72% annotation accuracy for celltypeEnrich, generally outperforming other tools, which had either lower accuracy, incomplete tissue coverage, or the need for parameter optimization. The performance of celltypeEnrich remained stable when input gene lists were down-sampled to 25% of their original size. Availability and Implementation celltypeEnrich is freely available at (https://celltypeenrich.gdcb.iastate.edu) as an R Shiny web application under the MIT license for non-profit academic use.
ER -