CellMentor
Supervised Non-negative Matrix Factorization for Dimensional Reduction in Single-Cell Analysis
Bioconductor version: 3.23 · Package version: 1.0.1
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("CellMentor") Details
| Maintainer | Ekaterina Petrenko <petrenko.kate@icloud.com> |
| Author | Ekaterina Petrenko [aut, cre] (ORCID: <https://orcid.org/0000-0003-3549-834X>) |
| License | Apache License (>= 2) |
| URL | https://github.com/petrenkokate/CellMentor |
| Bug Reports | https://github.com/petrenkokate/CellMentor/issues |
| Downloads rank | 68 |
| Source branch | RELEASE_3_23 |
| biocViews | DimensionReduction, SingleCell, Software, Transcriptomics |
Documentation
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Dependencies
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
Suggests: testthat (>= 3.0.0), covr, withr, rmarkdown, knitr, BiocStyle, scater, scRNAseq