CellMentor
This is the released version of CellMentor; for the devel version, see CellMentor.
Supervised Non-negative Matrix Factorization for Dimensional Reduction in Single-Cell Analysis
Bioconductor version: Release (3.23)
Implements supervised cell type-aware non-negative matrix factorization (NMF) for dimensional reduction in single-cell RNA sequencing analysis. The package provides methods for incorporating cell type information into the dimensionality reduction process, enabling improved visualization and downstream analysis of single-cell data while preserving biological structure. CellMentor employs a unique loss function that simultaneously minimizes variation within known cell populations while maximizing distinctions between different cell types, enabling effective transfer of learned patterns from labeled reference datasets to new unlabeled data.
Author: Ekaterina Petrenko [aut, cre] 
Maintainer: Ekaterina Petrenko <petrenko.kate at icloud.com>
citation("CellMentor")):Ekaterina Petrenko. CellMentor: Supervised Non-negative Matrix Factorization for Dimensional Reduction in Single-Cell Analysis. doi:10.18129/B9.bioc.CellMentor, R package version 1.0.1, https://bioconductor.org/packages/CellMentor.
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("CellMentor")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("CellMentor")| Introduction to CellMentor | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | DimensionReduction, SingleCell, Software, Transcriptomics |
| Version | 1.0.1 |
| In Bioconductor since | BioC 3.23 (R-4.6) (< 6 months) |
| License | Apache License (>= 2) |
| Depends | R (>= 4.5.0) |
| Imports | methods, Matrix, BiocParallel, SingleR, Seurat (>= 4.0.0), utils, stats, parallel, progress, ggplot2, data.table, magrittr, graphics, RMTstat, sparsesvd, cluster, skmeans, MLmetrics, tibble, lsa, nnls, SingleCellExperiment, entropy, irlba, aricode |
| System Requirements | |
| URL | https://github.com/petrenkokate/CellMentor |
| Bug Reports | https://github.com/petrenkokate/CellMentor/issues |
See More
| Suggests | testthat (>= 3.0.0), covr, withr, rmarkdown, knitr, BiocStyle, scater, scRNAseq |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report, r-universe |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | CellMentor_1.0.1.tar.gz |
| Windows Binary (x86_64) | CellMentor_1.0.1.zip |
| macOS Binary (big-sur-x86_64) | CellMentor_1.0.1.tgz |
| macOS Binary (sonoma-arm64) | CellMentor_1.0.1.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/CellMentor |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/CellMentor |
| Package Short Url | https://bioconductor.org/packages/CellMentor/ |
| Package Downloads Report | Download Stats |
| Old Source Packages for BioC 3.23 | Source Archive |