sincell
This is the released version of sincell; for the devel version, see sincell.
R package for the statistical assessment of cell state hierarchies from single-cell RNA-seq data
Bioconductor version: Release (3.23)
Cell differentiation processes are achieved through a continuum of hierarchical intermediate cell-states that might be captured by single-cell RNA seq. Existing computational approaches for the assessment of cell-state hierarchies from single-cell data might be formalized under a general workflow composed of i) a metric to assess cell-to-cell similarities (combined or not with a dimensionality reduction step), and ii) a graph-building algorithm (optionally making use of a cells-clustering step). Sincell R package implements a methodological toolbox allowing flexible workflows under such framework. Furthermore, Sincell contributes new algorithms to provide cell-state hierarchies with statistical support while accounting for stochastic factors in single-cell RNA seq. Graphical representations and functional association tests are provided to interpret hierarchies.
Author: Miguel Julia <migueljuliamolina at gmail.com>, Amalio Telenti <atelenti at jcvi.org>, Antonio Rausell <antonio.rausell at institutimagine.org>
Maintainer: Miguel Julia <migueljuliamolina at gmail.com>, Antonio Rausell<antonio.rausell at institutimagine.org>
citation("sincell")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("sincell")
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("sincell")| Sincell: Analysis of cell state hierarchies from single-cell RNA-seq | R Script | |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | BiomedicalInformatics, CellBiology, Clustering, FunctionalGenomics, GeneExpression, GeneSetEnrichment, GraphAndNetwork, ImmunoOncology, RNASeq, Sequencing, Software, SystemsBiology, Visualization |
| Version | 1.44.0 |
| In Bioconductor since | BioC 3.1 (R-3.2) (11.5 years) |
| License | GPL (>= 2) |
| Depends | R (>= 3.0.2), igraph |
| Imports | Rcpp (>= 0.11.2), entropy, scatterplot3d, MASS, TSP, ggplot2, reshape2, fields, proxy, parallel, Rtsne, fastICA, cluster, statmod |
| System Requirements | |
| URL | http://bioconductor.org/ |
See More
| Suggests | BiocStyle, knitr, biomaRt, stringr, monocle |
| Linking To | Rcpp |
| 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 | sincell_1.44.0.tar.gz |
| Windows Binary (x86_64) | sincell_1.44.0.zip |
| macOS Binary (big-sur-x86_64) | sincell_1.44.0.tgz |
| macOS Binary (sonoma-arm64) | sincell_1.44.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/sincell |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/sincell |
| Bioc Package Browser | https://code.bioconductor.org/browse/sincell/ |
| Package Short Url | https://bioconductor.org/packages/sincell/ |
| Package Downloads Report | Download Stats |
| Old Source Packages for BioC 3.23 | Source Archive |