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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=scISR to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4