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ccfindR

This is the released version of ccfindR; for the devel version, see ccfindR.

All versions 3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10, 3.9, 3.8, 3.7

Cancer Clone Finder


Bioconductor version: Release (3.23)

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")):

Jun Woo, Jinhua Wang. ccfindR: Cancer Clone Finder. doi:10.18129/B9.bioc.ccfindR, R package version 1.32.0, https://bioconductor.org/packages/ccfindR.

Generated from the package metadata; it may differ from the package's own citation.

Installation

To install this package, start R (version "4.6") 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 ManualPDF
NEWSText

Details

biocViews Bayesian, Clustering, ImmunoOncology, SingleCell, Software, Transcriptomics
Version1.32.0
In Bioconductor sinceBioC 3.7 (R-3.5) (8.5 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
URLhttp://dx.doi.org/10.26508/lsa.201900443
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Suggests BiocStyle, knitr, rmarkdown
Linking To Rcpp, RcppEigen
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Package Archives

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

Source Package ccfindR_1.32.0.tar.gz
Windows Binary (x86_64) ccfindR_1.32.0.zip
macOS Binary (big-sur-x86_64)
macOS Binary (sonoma-arm64)
Source Repositorygit 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/
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