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Bioconductor 3.22 Released

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peco

This is thereleased version of peco; for the devel version, seepeco.

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

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DOI: 10.18129/B9.bioc.peco


Bioconductor version: Release (3.22)

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, entercitation("peco")):

Installation

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

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

For older versions of R, please refer to the appropriateBioconductor 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 pecoHTMLR Script
Reference ManualPDF
NEWSText

Need some help? Ask on the Bioconductor Support site!

Details

biocViewsClassification,GeneExpression,RNASeq,Sequencing,SingleCell,Software,StatisticalMethod,Transcriptomics,Visualization
Version1.22.0
In Bioconductor sinceBioC 3.11 (R-4.0) (5.5 years)
LicenseGPL (>= 3)
DependsR (>= 3.5.0)
Importsassertthat,circular,conicfit,doParallel,foreach,genlasso (>= 1.4), graphics, methods, parallel,scater,SingleCellExperiment,SummarizedExperiment, stats, utils
System Requirements
URLhttps://github.com/jhsiao999/peco
Bug Reportshttps://github.com/jhsiao999/peco/issues
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Package Archives

FollowInstallation instructions to use this package in your R session.

Source Packagepeco_1.22.0.tar.gz
Windows Binary (x86_64) peco_1.22.0.zip (64-bit only)
macOS Binary (x86_64)peco_1.22.0.tgz
macOS Binary (arm64)peco_1.22.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/peco
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/peco
Bioc Package Browserhttps://code.bioconductor.org/browse/peco/
Package Short Urlhttps://bioconductor.org/packages/peco/
Package Downloads ReportDownload Stats

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