Package: scISR 0.1.1

Duc Tran

scISR: Single-Cell Imputation using Subspace Regression

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>).

Authors:Duc Tran [aut, cre], Bang Tran [aut], Hung Nguyen [aut], Tin Nguyen [fnd]

scISR_0.1.1.tar.gz
scISR_0.1.1.zip(r-4.7)scISR_0.1.1.zip(r-4.6)scISR_0.1.1.zip(r-4.5)
scISR_0.1.1.tgz(r-4.6-any)scISR_0.1.1.tgz(r-4.5-any)
scISR_0.1.1.tar.gz(r-4.7-any)scISR_0.1.1.tar.gz(r-4.6-any)
scISR_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
scISR/json (API)

# Install 'scISR' in R:

install.packages('scISR', repos = c('https://duct317.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/duct317/scisr/issues

Datasets:

Goolam - Goolam

On CRAN:

4.18 score 3 stars 8 scripts 173 downloads 1 exports 21 dependencies

Last updated from:b25eac4ad6. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	148
source / vignettes	OK	196
linux-release-x86_64	NOTE	158
macos-release-arm64	NOTE	165
macos-oldrel-arm64	NOTE	164
windows-devel	NOTE	98
windows-release	NOTE	85
windows-oldrel	NOTE	75
wasm-release	OK	130