scCircaSim: A Circadian Simulator for Single-Cell and Spatial Transcriptomics
- 1Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, China
Abstract
Motivation: Simulated single-cell and spatial transcriptomic datasets that capture circadian dynamics while providing known ground truth remain scarce, limiting systematic evaluation of circadian analysis methods. Results: We developed scCircaSim to generate circadian single-cell and spatial transcriptomic data from a single-time-point reference. The framework combines phase progression with reference-derived network propagation of anchor gene rhythms and incorporates neighborhood effects for spatial simulation. Outputs retain reference heterogeneity and provide known cell or spot phases, rhythmicity labels, and gene-level mesor, amplitude, and phase values. Validation showed retention of reference structure and recovery of specified temporal patterns. Benchmarks of four cell phase inference methods and three rhythmic gene analysis methods revealed differences in phase accuracy, rhythmicity detection, and parameter recovery. scCircaSim supports reproducible method evaluation and preliminary experimental planning. Availability and Implementation: scCircaSim is implemented in R and available at https://github.com/Liwei-DynamicsLab/scCircaSim.
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BibTeX
@misc{li2026sccircasim,
title = {{scCircaSim: A Circadian Simulator for Single-Cell and Spatial Transcriptomics}},
author = {C. Li and L. Zhang and Q. Zhang and L. Zhao and X. Song and Y. Tian and G. Tang and H. Zhou and Z. Wang and P. Sun},
howpublished = {bioRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.05.764753},
url = {https://www.biorxiv.org/content/10.64898/2026.11.05.764753v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - scCircaSim: A Circadian Simulator for Single-Cell and Spatial Transcriptomics
AU - C. Li
AU - L. Zhang
AU - Q. Zhang
AU - L. Zhao
AU - X. Song
AU - Y. Tian
AU - G. Tang
AU - H. Zhou
AU - Z. Wang
AU - P. Sun
PY - 2026
DA - 2026/11/05
PB - bioRxiv
DO - 10.64898/2026.11.05.764753
UR - https://www.biorxiv.org/content/10.64898/2026.11.05.764753v1
AB - Motivation: Simulated single-cell and spatial transcriptomic datasets that capture circadian dynamics while providing known ground truth remain scarce, limiting systematic evaluation of circadian analysis methods. Results: We developed scCircaSim to generate circadian single-cell and spatial transcriptomic data from a single-time-point reference. The framework combines phase progression with reference-derived network propagation of anchor gene rhythms and incorporates neighborhood effects for spatial simulation. Outputs retain reference heterogeneity and provide known cell or spot phases, rhythmicity labels, and gene-level mesor, amplitude, and phase values. Validation showed retention of reference structure and recovery of specified temporal patterns. Benchmarks of four cell phase inference methods and three rhythmic gene analysis methods revealed differences in phase accuracy, rhythmicity detection, and parameter recovery. scCircaSim supports reproducible method evaluation and preliminary experimental planning. Availability and Implementation: scCircaSim is implemented in R and available at https://github.com/Liwei-DynamicsLab/scCircaSim.
ER -