RT Journal Article
SR Electronic
T1 Cell Layers: Uncovering clustering structure and knowledge in unsupervised single-cell transcriptomic analysis
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.11.29.400614
DO 10.1101/2020.11.29.400614
A1 Andrew P. Blair
A1 Robert K. Hu
A1 Elie N. Farah
A1 Neil C. Chi
A1 Katherine S. Pollard
A1 Pawel F. Przytycki
A1 Irfan S. Kathiriya
A1 Benoit G. Bruneau
YR 2020
UL http://biorxiv.org/content/early/2020/11/30/2020.11.29.400614.abstract
AB Motivation Unsupervised clustering of single-cell transcriptomics is a powerful method for identifying cell populations. Static visualization techniques for single-cell clustering only display results for a single resolution parameter. Analysts will often evaluate more than one resolution parameter, but then only report one.Results We developed Cell Layers, an interactive Sankey tool for the quantitative investigation of gene expression, coexpression, biological processes, and cluster integrity across clustering resolutions. Cell Layers enhances the interpretability of single-cell clustering by linking molecular data and cluster evaluation metrics, to provide novel insight into cell populations.Availability and implementation Upon requestCompeting Interest StatementA.P.B is a consultant of Genentech, a member of Roche. B.G.B. is a co-founder and shareholder of Tenaya Therapeutics. K.S.P. is a shareholder of Tenaya Therapeutics. None of the work presented here is related to the interests of Genentech or Tenaya Therapeutics.