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tricycle: Transferable Representation and Inference of cell cycle

Bioconductor version: Release (3.19)

The package contains functions to infer and visualize cell cycle process using Single Cell RNASeq data. It exploits the idea of transfer learning, projecting new data to the previous learned biologically interpretable space. We provide a pre-learned cell cycle space, which could be used to infer cell cycle time of human and mouse single cell samples. In addition, we also offer functions to visualize cell cycle time on different embeddings and functions to build new reference.

Author: Shijie Zheng [aut, cre]

Maintainer: Shijie Zheng <shijieczheng at>

Citation (from within R, enter citation("tricycle")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

tricycle: Transferable Representation and Inference of Cell Cycle HTML R Script
Reference Manual PDF


biocViews BiologicalQuestion, DimensionReduction, ImmunoOncology, RNASeq, SingleCell, Software, Transcription, Transcriptomics
Version 1.12.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License GPL-3
Depends R (>= 4.0), SingleCellExperiment
Imports methods, circular, ggplot2, ggnewscale, AnnotationDbi, scater, GenomicRanges, IRanges, S4Vectors, scattermore, dplyr, RColorBrewer, grDevices, stats, SummarizedExperiment, utils
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Suggests testthat (>= 3.0.0), BiocStyle, knitr, rmarkdown, CircStats, cowplot, htmltools, Seurat,,
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Follow Installation instructions to use this package in your R session.

Source Package tricycle_1.12.0.tar.gz
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macOS Binary (x86_64) tricycle_1.12.0.tgz
macOS Binary (arm64) tricycle_1.12.0.tgz
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