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scISR  

Single-Cell Imputation using Subspace Regression
View on CRAN: Click here


Download and install scISR package within the R console
Install from CRAN:
install.packages("scISR")

Install from Github:
library("remotes")
install_github("cran/scISR")

Install by package version:
library("remotes")
install_version("scISR", "0.1.1")



Attach the package and use:
library("scISR")
Maintained by
Duc Tran
[Scholar Profile | Author Map]
First Published: 2022-06-30
Latest Update: 2022-06-30
Description:
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) ).
How to cite:
Duc Tran (2022). scISR: Single-Cell Imputation using Subspace Regression. R package version 0.1.1, https://cran.r-project.org/web/packages/scISR. Accessed 29 Mar. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited scISR R package
View scISR citation profile
Other R packages that scISR depends, imports, suggests or enhances
Complete documentation for scISR
Functions, R codes and Examples using the scISR R package
Some associated functions: Goolam . scISR . 
Some associated R codes: PerturbationClustering.R . Util.R . scISR.R .  Full scISR package functions and examples
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