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).">

umap: Uniform Manifold Approximation and Projection (original) (raw)

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
BugReports: https://github.com/tkonopka/umap/issues
License: MIT + file
URL: https://github.com/tkonopka/umap
NeedsCompilation: yes
CRAN checks: umap results

Documentation:

Downloads:

Reverse dependencies:

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

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