umap: Uniform Manifold Approximation and Projection

Uniform manifold approximation and projection is a technique for dimension reduction. The algorithm was described by McInnes and Healy (2018) in <doi:10.48550/arXiv.1802.03426>. This package provides an interface for two implementations. One is written from scratch, including components for nearest-neighbor search and for embedding. The second implementation is a wrapper for 'python' package 'umap-learn' (requires separate installation, see vignette for more details).

Version:	0.2.10.0
Depends:	R (≥ 3.6.0)
Imports:	Matrix, methods, openssl, reticulate, Rcpp (≥ 0.12.6), RSpectra, stats
LinkingTo:	Rcpp
Suggests:	knitr, rmarkdown, testthat
Published:	2023-02-01
DOI:	10.32614/CRAN.package.umap
Author:	Tomasz Konopka [aut, cre]
Maintainer:	Tomasz Konopka <tokonopka at gmail.com>
BugReports:	https://github.com/tkonopka/umap/issues
License:	MIT + file LICENSE
URL:	https://github.com/tkonopka/umap
NeedsCompilation:	yes
CRAN checks:	umap results

Documentation:

Reference manual:	umap.pdf
Vignettes:	Uniform Manifold Approximation and Projection in R Interfacing with 'umap-learn'

Downloads:

Package source:	umap_0.2.10.0.tar.gz
Windows binaries:	r-devel: umap_0.2.10.0.zip, r-release: umap_0.2.10.0.zip, r-oldrel: umap_0.2.10.0.zip
macOS binaries:	r-release (arm64): umap_0.2.10.0.tgz, r-oldrel (arm64): umap_0.2.10.0.tgz, r-release (x86_64): umap_0.2.10.0.tgz, r-oldrel (x86_64): umap_0.2.10.0.tgz
Old sources:	umap archive

Reverse dependencies:

Reverse depends:	KODAMA
Reverse imports:	animalcules, CelliD, chameleon, ChromSCape, COTAN, EmbedSOM, FateID, GEOexplorer, ggpca, HIPPO, HVT, ILoReg, InterCellar, jrSiCKLSNMF, karyotapR, M3C, MatrixQCvis, Mercator, musclesyneRgies, nevada, PhyloProfile, PIUMA, projectR, RaceID, RCSL, regioneReloaded, rrvgo, RSDA, scDataviz, scDesign3, sRACIPE, SuperCell, theftdlc, tomoda
Reverse suggests:	cola, crosshap, dimRed, HDCytoData, NGCHM, OlinkAnalyze, OTclust, pctax, Platypus, ProjectionBasedClustering, qeML, quollr, scPipe, seriation, SPIAT, UCSCXenaShiny

Linking:

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