Nicola Licheri

The paper evaluates the sparsely-connected autoencoder (SCA) for functional mining of single-cell RNA-seq clusters, showing its ability to uncover hidden features and improve cluster reconstruction.

rCASC provides a reproducible RNA-seq analysis workflow for single-cell data, enabling functional and computational reproducibility from counts generation to cell sub-population signature identification.