SISUA: SemI-SUpervised generative Autoencoder for single cell data
Trung Ngô Trọng, Roger Kramer, Juha Mehtonen, Gerardo González, Ville Hautamäki, Merja Heinäniemi
The paper introduces a semi-supervised generative model for single-cell data using CITE-seq protein counts to improve gene expression analysis.
bioRxiv · May 8, 2019 · PreprintBioinformatics