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 <[email protected]>
LicenseGPL-3
Version1.2.0
URL https://github.com/quon-titative-biology/scAlign
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("scAlign")

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scAlign documentation built on Oct. 31, 2019, 3:34 a.m.