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 dataBioconductor version: Development (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")
# 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.
DocumentationTo 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 1.21.0 In Bioconductor since BioC 3.11 (R-4.0) (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 Package Archives
Follow Installation instructions to use this package in your R session.
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