scAlign: An alignment and integration method for single cell genomics

An unsupervised deep learning method for data alignment, integration and estimation of per-cell differences in -omic data (e.g. gene expression) across datasets (conditions, tissues, species). See Johansen and Quon (2019) <doi:10.1101/504944> for more details.

Package details

AuthorNelson Johansen [aut, cre], Gerald Quon [aut]
Bioconductor views DimensionReduction NeuralNetwork SingleCell Transcriptomics
MaintainerNelson Johansen <>
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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scAlign documentation built on April 28, 2020, 6:10 p.m.