peco

DOI: 10.18129/B9.bioc.peco    

This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see peco.

A Supervised Approach for **P**r**e**dicting **c**ell Cycle Pr**o**gression using scRNA-seq data

Bioconductor version: 3.12

Our approach provides a way to assign continuous cell cycle phase using scRNA-seq data, and consequently, allows to identify cyclic trend of gene expression levels along the cell cycle. This package provides method and training data, which includes scRNA-seq data collected from 6 individual cell lines of induced pluripotent stem cells (iPSCs), and also continuous cell cycle phase derived from FUCCI fluorescence imaging data.

Author: Chiaowen Joyce Hsiao [aut, cre], Matthew Stephens [aut], John Blischak [ctb], Peter Carbonetto [ctb]

Maintainer: Chiaowen Joyce Hsiao <joyce.hsiao1 at gmail.com>

Installation

To install this package, start R (version "4.0") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("peco")

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

Documentation

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

browseVignettes("peco")

 

HTML	R Script	An example of predicting cell cycle phase using peco
PDF		Reference Manual
Text		NEWS

Details

biocViews	Classification, GeneExpression, RNASeq, Sequencing, SingleCell, Software, StatisticalMethod, Transcriptomics, Visualization
Version	1.2.0
In Bioconductor since	BioC 3.11 (R-4.0) (1 year)
License	GPL (>= 3)
Depends	R (>= 2.10)
Imports	assertthat, circular, conicfit, doParallel, foreach, genlasso (>= 1.4), graphics, methods, parallel, scater, SingleCellExperiment, SummarizedExperiment, stats, utils
LinkingTo
Suggests	knitr, rmarkdown
SystemRequirements
Enhances
URL	https://github.com/jhsiao999/peco
BugReports	https://github.com/jhsiao999/peco/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	peco_1.2.0.tar.gz
Windows Binary	peco_1.2.0.zip
macOS 10.13 (High Sierra)	peco_1.2.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/peco
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/peco
Package Short Url	https://bioconductor.org/packages/peco/
Package Downloads Report	Download Stats