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 <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
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
Old sources: umap archive

Reverse dependencies:

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

Linking:

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