README.md

In bangtran365/scISR: Single-cell Imputation using Subspace Regression

scISR: Single-cell Imputation using Subspace Regression

scISR performs imputation for single-cell sequencing data. scISR identifies the true dropout values in the scRNA-seq dataset using hyper-geomtric testing approach. Based on the result obtained from hyper-geometric testing, the original dataset is segregated into two including training data and imputable data. Next, training data is used for constructing a generalize linear regression model that is used for imputation on the imputable data.

How to install

• The package can be installed from this repository.
• Install devtools: utils::install.packages('devtools')
• Install the package using: devtools::install_github('bangtran365/scISR')

Example

• Load the sample dataset scISRExample: data(scISRExample)
• Perform the : imputed <- scISR(data = scISRExample$dropout)
• Plot the complete data: plotscISR(scISRExample$raw, label = scISRExample$celltype)
• Plot the dropout data: plotscISR(scISRExample$dropout, label = scISRExample$celltype)
• Plot the imputed data: plotscISR(imputed, label = scISRExample$celltype)

bangtran365/scISR documentation built on Jan. 20, 2021, 12:24 a.m.