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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 |
Reference manual: | scISR.pdf |
Vignettes: |
scISR package manual |
Package source: | scISR_0.1.1.tar.gz |
Windows binaries: | r-devel: scISR_0.1.1.zip, r-release: scISR_0.1.1.zip, r-oldrel: scISR_0.1.1.zip |
macOS binaries: | r-release (arm64): scISR_0.1.1.tgz, r-oldrel (arm64): scISR_0.1.1.tgz, r-release (x86_64): scISR_0.1.1.tgz, r-oldrel (x86_64): scISR_0.1.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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