peco

This is the released version of peco; for the devel version, see peco.

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


Bioconductor version: Release (3.20)

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 "4.4") and enter:


if (!require("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")
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 1.18.0
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
See More
Suggests knitr, rmarkdown
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package peco_1.18.0.tar.gz
Windows Binary (x86_64) peco_1.18.0.zip (64-bit only)
macOS Binary (x86_64) peco_1.18.0.tgz
macOS Binary (arm64) peco_1.18.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/peco
Source Repository (Developer Access) git clone [email protected]:packages/peco
Bioc Package Browser https://code.bioconductor.org/browse/peco/
Package Short Url https://bioconductor.org/packages/peco/
Package Downloads Report Download Stats