uwot: The Uniform Manifold Approximation and Projection (UMAP) Method
for Dimensionality Reduction
An implementation of the Uniform Manifold Approximation and
Projection dimensionality reduction by McInnes et al. (2018)
<arXiv:1802.03426>. It also provides means to transform new data and to
carry out supervised dimensionality reduction. An implementation of the
related LargeVis method of Tang et al. (2016) <arXiv:1602.00370> is also
provided. This is a complete re-implementation in R (and C++, via the 'Rcpp'
package): no Python installation is required. See the uwot website
(<https://github.com/jlmelville/uwot>) for more documentation and examples.
Version: |
0.1.10 |
Depends: |
Matrix |
Imports: |
Rcpp, methods, FNN, RSpectra, RcppAnnoy (≥ 0.0.17), irlba |
LinkingTo: |
Rcpp, RcppProgress, RcppAnnoy, dqrng |
Suggests: |
testthat, covr |
Published: |
2020-12-15 |
Author: |
James Melville [aut, cre],
Aaron Lun [ctb],
Mohamed Nadhir Djekidel [ctb],
Yuhan Hao [ctb] |
Maintainer: |
James Melville <jlmelville at gmail.com> |
BugReports: |
https://github.com/jlmelville/uwot/issues |
License: |
GPL (≥ 3) |
URL: |
https://github.com/jlmelville/uwot |
NeedsCompilation: |
yes |
Materials: |
NEWS |
CRAN checks: |
uwot results |
Downloads:
Reverse dependencies:
Reverse imports: |
celda, CiteFuse, embed, EmbedSOM, iCellR, infinityFlow, MOFA2, mumosa, musicatk, pipeComp, rliger, sccore, scDHA, Seurat, singleCellTK |
Reverse suggests: |
CATALYST, celltrackR, conos, curatedMetagenomicData, densvis, DepecheR, doc2vec, dyndimred, dynplot, healthyR, iSEEu, miloR, netSmooth, pagoda2, ProjectionBasedClustering, SCArray, scater, scp, SingleCellMultiModal, slingshot, tidySingleCellExperiment |
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=uwot
to link to this page.