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).
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, TOmicsVis, tomoda |
Reverse suggests: |
cola, crosshap, dimRed, HDCytoData, NGCHM, OlinkAnalyze, OTclust, pctax, ProjectionBasedClustering, qeML, quollr, scPipe, seriation, SPIAT, UCSCXenaShiny |
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