Single cell HSNE paper published in Nature Communications27 Nov 2017
We are excited to announce that our paper Visual Analysis of Mass Cytometry Data by Hierarchical Stochastic Neighbor Embedding Reveals Rare Cell Types, previously available on BiorXiv has been published in Nature Communications. The paper describes the application of HSNE, a hierarchical SNE-based technique that allows the exploration of datasets too large for other SNE-based techniques (such as t-SNE) through a hierarchical representation, to single cell mass cytometry data. See the movie below for an exemplary exploration of a dataset consisting of 5 Million cells.
Along with the paper we released a major update for our single cell analysis software Cytosplore now featuring HSNE alongside A-tSNE and SPADE for single cell analysis. The software is available for free to download at https://www.cytosplore.org