R package for modeling single cell UMI expression data using regularized negative binomial regression
This packaged was developed by Christoph Hafemeister in Rahul Satija's lab at the New York Genome Center. A previous version of this work was used in the paper Developmental diversification of cortical inhibitory interneurons, Nature 555, 2018. We are currently working on integrating the functionality of this package into Seurat, an R package designed for QC, analysis, and exploration of single cell RNA-seq data.
This package is in beta status, please sanity check any results, and notify me of any issues you find.
devtools::install_github(repo = 'ChristophH/sctransform')
normalized_data <- sctransform::vst(umi_count_matrix)$y
For usage examples see vignettes in inst/doc or use the built-in help after installation
?sctransform::vst
browseVignettes(package = 'sctransform')
Available vignettes:
Variance stabilizing transformation
Differential expression
Batch correction
Denoising