This is the development version of ccfindR; for the stable release version, see ccfindR.
Cancer Clone FinderBioconductor version: Development (3.22)
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 (from within R, entercitation("ccfindR")
): 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("ccfindR")
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("ccfindR")
ccfindR: single-cell RNA-seq analysis using Bayesian non-negative matrix factorization HTML R Script Reference Manual PDF NEWS Text Details biocViews Bayesian, Clustering, ImmunoOncology, SingleCell, Software, Transcriptomics Version 1.29.0 In Bioconductor since BioC 3.7 (R-3.5) (7 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 Package Archives
Follow Installation instructions to use this package in your R session.
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