peco is a supervised approach for predicting continuous cell cycle phase in single-cell RNA-seq (scRNA-seq) data analysis.
We trained peco using cyclic gene expression signatures learned from Fluorescence Ubiquitin Cell Cycle Indicator (FUCCI) reporters. The data was collected from fluorescence imaging with scRNA-seq to measure cell cycle phase and gene expression levels in human induced pluripotent stem cells (iPSCs).
- Our paper: Characterizing and inferring quantitative cell-cycle phase in single-cell RNA-seq data analysis.
- peco 0.99.4 is submitted and pending review on Bioconductor.
The development version can be downloaded from GitHub
devtools::install_github("jhsiao999/peco")
library(peco)
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GEO record GSE121265 for all raw and processed sequencing data
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The processed data data sets are also available in as a gzip compressed tarball on the Gilad lab website: https://giladlab.uchicago.edu/wp-content/uploads/2019/02/Hsiao_et_al_2019.tar.gz.
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All data sets used in our analysis are listed and downloadable at https://jdblischak.github.io/fucci-seq/data-overview.html.
Find out how we
Please contact me at [email protected] for questions on the package or the methods.
Chiaowen Joyce Hsiao, PoYuan Tung, John D. Blischak, Jonathan E. Burnett, Kenneth A. Barr, Kushal K. Dey, Matthew Stephens and Yoav Gilad (2020). Characterizing and inferring quantitative cell cycle phase in single-cell RNA-seq data analysis. Genome Biology, 30(4): 611-621, doi:10.1101/gr.247759.11
Copyright (c) 2018-2019, Chiaowen Joyce Hsiao.
All source code and software in this repository are made available under the terms of the GNU General Public License. See file LICENSE for the full text of the license.