peco

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

A Supervised Approach for Predicting cell Cycle Progression using scRNA-seq data

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DOI: 10.18129/B9.bioc.peco

Bioconductor version: Development (3.23)

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 "4.6") 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

Need some help? Ask on the Bioconductor Support site!

Details

biocViews Classification, GeneExpression, RNASeq, Sequencing, SingleCell, Software, StatisticalMethod, Transcriptomics, Visualization

Version 1.23.0

In Bioconductor since BioC 3.11 (R-4.0) (5.5 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

Suggests knitr, rmarkdown

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Package Archives

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

Source Package peco_1.23.0.tar.gz

Windows Binary (x86_64)

macOS Binary (x86_64) peco_1.23.0.tgz

macOS Binary (arm64) peco_1.23.0.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/

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