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 |