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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