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.
|Author||Nelson Johansen [aut, cre], Gerald Quon [aut]|
|Bioconductor views||DimensionReduction NeuralNetwork SingleCell Transcriptomics|
|Maintainer||Nelson Johansen <[email protected]>|
|Package repository||View on Bioconductor|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.