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R package for modeling single cell UMI expression data using regularized negative binomial regression
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README.md

sctransform

R package for normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression

This packaged was developed by Christoph Hafemeister in Rahul Satija's lab at the New York Genome Center. Core functionality of this package has been integrated into Seurat, an R package designed for QC, analysis, and exploration of single cell RNA-seq data.

Quick start

devtools::install_github(repo = 'ChristophH/sctransform')
normalized_data <- sctransform::vst(umi_count_matrix)$y

Help

For usage examples see vignettes in inst/doc or use the built-in help after installation
?sctransform::vst

Available vignettes:
Variance stabilizing transformation
Using sctransform in Seurat

Reference

Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. bioRxiv 576827 (2019). doi:10.1101/576827

An early version of this work was used in the paper Developmental diversification of cortical inhibitory interneurons, Nature 555, 2018.

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