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Cancer Clone Finder

Bioconductor version: Release (3.19)

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>

Citation (from within R, enter citation("ccfindR")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

ccfindR: single-cell RNA-seq analysis using Bayesian non-negative matrix factorization HTML R Script
Reference Manual PDF


biocViews Bayesian, Clustering, ImmunoOncology, SingleCell, Software, Transcriptomics
Version 1.24.0
In Bioconductor since BioC 3.7 (R-3.5) (6 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)
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Suggests BiocStyle, knitr, rmarkdown
Linking To Rcpp, RcppEigen
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Follow Installation instructions to use this package in your R session.

Source Package ccfindR_1.24.0.tar.gz
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