ccfindR
Cancer Clone Finder
Bioconductor version: Release (3.20)
A collection of tools for cancer genomic data clustering analyses, including those for single cell RNA-seq. Cell clustering and feature gene selection analysis employ Bayesian (and maximum likelihood) non-negative matrix factorization (NMF) algorithm. Input data set consists of RNA count matrix, gene, and cell bar code annotations. Analysis outputs are factor matrices for multiple ranks and marginal likelihood values for each rank. The package includes utilities for downstream analyses, including meta-gene identification, visualization, and construction of rank-based trees for clusters.
Author: Jun Woo [aut, cre], Jinhua Wang [aut]
Maintainer: Jun Woo <jwoo at umn.edu>
citation("ccfindR")):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ccfindR")
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("ccfindR")| ccfindR: single-cell RNA-seq analysis using Bayesian non-negative matrix factorization | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Bayesian, Clustering, ImmunoOncology, SingleCell, Software, Transcriptomics |
| Version | 1.26.0 |
| In Bioconductor since | BioC 3.7 (R-3.5) (6.5 years) |
| License | GPL (>= 2) |
| Depends | R (>= 3.6.0) |
| Imports | stats, S4Vectors, utils, methods, Matrix, SummarizedExperiment, SingleCellExperiment, Rtsne, graphics, grDevices, gtools, RColorBrewer, ape, Rmpi, irlba, Rcpp, Rdpack (>= 0.7) |
| System Requirements | |
| URL | http://dx.doi.org/10.26508/lsa.201900443 |
See More
| Suggests | BiocStyle, knitr, rmarkdown |
| Linking To | Rcpp, RcppEigen |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | MutationalPatterns |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | ccfindR_1.26.0.tar.gz |
| Windows Binary (x86_64) | ccfindR_1.26.0.zip |
| macOS Binary (x86_64) | |
| macOS Binary (arm64) | |
| Source Repository | git clone https://git.bioconductor.org/packages/ccfindR |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/ccfindR |
| Bioc Package Browser | https://code.bioconductor.org/browse/ccfindR/ |
| Package Short Url | https://bioconductor.org/packages/ccfindR/ |
| Package Downloads Report | Download Stats |