ccfindR

DOI: 10.18129/B9.bioc.ccfindR    

This is the development version of ccfindR; to use it, please install the devel version of Bioconductor.

Cancer Clone Finder

Bioconductor version: Development (3.10)

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, enter citation("ccfindR")):

Installation

To install this package, start R (version "3.6") and enter:

if (!requireNamespace("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.

Documentation

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

browseVignettes("ccfindR")

 

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

Details

biocViews Bayesian, Clustering, ImmunoOncology, SingleCell, Software, Transcriptomics
Version 1.5.1
In Bioconductor since BioC 3.7 (R-3.5) (1.5 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)
LinkingTo Rcpp, RcppEigen
Suggests BiocStyle, knitr, rmarkdown
SystemRequirements
Enhances
URL http://dx.doi.org/10.26508/lsa.201900443
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package ccfindR_1.5.1.tar.gz
Windows Binary ccfindR_1.5.1.zip
Mac OS X 10.11 (El Capitan) ccfindR_1.5.1.tgz
Source Repository git clone https://git.bioconductor.org/packages/ccfindR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/ccfindR
Package Short Url https://bioconductor.org/packages/ccfindR/
Package Downloads Report Download Stats

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