peco

This is the development version of peco; for the stable release version, see peco.

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


Bioconductor version: Development (3.21)

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>

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

Installation

To install this package, start R (version "4.5") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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

Details

biocViews Classification, GeneExpression, RNASeq, Sequencing, SingleCell, Software, StatisticalMethod, Transcriptomics, Visualization
Version 1.19.0
In Bioconductor since BioC 3.11 (R-4.0) (4.5 years)
License GPL (>= 3)
Depends R (>= 3.5.0)
Imports assertthat, circular, conicfit, doParallel, foreach, genlasso (>= 1.4), graphics, methods, parallel, scater, SingleCellExperiment, SummarizedExperiment, stats, utils
System Requirements
URL https://github.com/jhsiao999/peco
Bug Reports https://github.com/jhsiao999/peco/issues
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Package Archives

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

Source Package peco_1.19.0.tar.gz
Windows Binary (x86_64) peco_1.19.0.zip
macOS Binary (x86_64) peco_1.19.0.tgz
macOS Binary (arm64) peco_1.19.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/peco
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/peco
Bioc Package Browser https://code.bioconductor.org/browse/peco/
Package Short Url https://bioconductor.org/packages/peco/
Package Downloads Report Download Stats