PINSPlus: Clustering Algorithm for Data Integration and Disease Subtyping

Provides a robust approach for omics data integration and disease subtyping. PINSPlus is fast and supports the analysis of large datasets with hundreds of thousands of samples and features. The software automatically determines the optimal number of clusters and then partitions the samples in a way such that the results are robust against noise and data perturbation (Nguyen et al. (2019) <doi:10.1093/bioinformatics/bty1049>, Nguyen et al. (2017)<doi:10.1101/gr.215129.116>, Nguyen et al. (2021)<doi:10.3389/fonc.2021.725133>).

Version: 2.0.6
Depends: R (≥ 2.10)
Imports: foreach, entropy , doParallel, matrixStats, Rcpp, RcppParallel, FNN, cluster, irlba, mclust, impute
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Suggests: knitr, rmarkdown, survival, markdown
Published: 2021-12-14
Author: Hung Nguyen, Bang Tran, Duc Tran and Tin Nguyen
Maintainer: Hung Nguyen <hungnp at nevada.unr.edu>
License: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL]
NeedsCompilation: yes
Citation: PINSPlus citation info
In views: Omics
CRAN checks: PINSPlus results

Documentation:

Reference manual: PINSPlus.pdf
Vignettes: PINSPlus

Downloads:

Package source: PINSPlus_2.0.6.tar.gz
Windows binaries: r-devel: PINSPlus_2.0.6.zip, r-release: PINSPlus_2.0.6.zip, r-oldrel: PINSPlus_2.0.6.zip
macOS binaries: r-release (arm64): PINSPlus_2.0.6.tgz, r-oldrel (arm64): PINSPlus_2.0.6.tgz, r-release (x86_64): PINSPlus_2.0.6.tgz
Old sources: PINSPlus archive

Reverse dependencies:

Reverse imports: scISR

Linking:

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