scDHA: Single-Cell Decomposition using Hierarchical Autoencoder

Provides a fast and accurate pipeline for single-cell analyses. The 'scDHA' software package can perform clustering, dimension reduction and visualization, classification, and time-trajectory inference on single-cell data (Tran et.al. (2021) <doi:10.1038/s41467-021-21312-2>).

Version: 1.2.0
Depends: R (≥ 3.4)
Imports: matrixStats, foreach, doParallel, igraph, Matrix, uwot, cluster, clusterCrit, Rcpp, RcppParallel, RcppAnnoy, methods, torch (≥ 0.3.0), RhpcBLASctl, coro
LinkingTo: Rcpp, RcppArmadillo, RcppParallel, RcppAnnoy
Suggests: testthat, knitr, mclust
Published: 2022-08-18
Author: Duc Tran [aut, cre], Tin Nguyen [fnd]
Maintainer: Duc Tran <duct at nevada.unr.edu>
BugReports: https://github.com/duct317/scDHA/issues
License: GPL-3
Copyright: see file COPYRIGHTS
URL: https://github.com/duct317/scDHA
NeedsCompilation: yes
Citation: scDHA citation info
Materials: README NEWS
CRAN checks: scDHA results

Documentation:

Reference manual: scDHA.pdf
Vignettes: scDHA package manual

Downloads:

Package source: scDHA_1.2.0.tar.gz
Windows binaries: r-devel: scDHA_1.2.0.zip, r-release: scDHA_1.2.0.zip, r-oldrel: scDHA_1.2.0.zip
macOS binaries: r-release (arm64): scDHA_1.2.0.tgz, r-oldrel (arm64): scDHA_1.2.0.tgz, r-release (x86_64): scDHA_1.2.0.tgz, r-oldrel (x86_64): scDHA_1.2.0.tgz
Old sources: scDHA archive

Reverse dependencies:

Reverse depends: scCAN

Linking:

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