Provides an imputation pipeline for single-cell RNA sequencing data. The 'scISR' method uses a hypothesis-testing technique to identify zero-valued entries that are most likely affected by dropout events and estimates the dropout values using a subspace regression model (Tran et.al. (2022) <doi:10.1038/s41598-022-06500-4>).
| Version: | 0.1.1 |
| Depends: | R (≥ 3.4) |
| Imports: | cluster,entropy, stats, utils, parallel,irlba,PINSPlus,matrixStats,markdown |
| Suggests: | testthat,knitr,mclust |
| Published: | 2022-06-30 |
| DOI: | 10.32614/CRAN.package.scISR |
| Author: | Duc Tran [aut, cre], Bang Tran [aut], Hung Nguyen [aut], Tin Nguyen [fnd] |
| Maintainer: | Duc Tran <duct at nevada.unr.edu> |
| BugReports: | https://github.com/duct317/scISR/issues |
| License: | LGPL-2 |LGPL-2.1 |LGPL-3 [expanded from: LGPL] |
| URL: | https://github.com/duct317/scISR |
| NeedsCompilation: | no |
| Citation: | scISR citation info |
| Materials: | README |
| CRAN checks: | scISR results |