A clustering-independent method for finding differentially expressed genes in single-cell transcriptome data

oleh: Alexis Vandenbon, Diego Diez

Format: Article
Diterbitkan: Nature Portfolio 2020-08-01

Deskripsi

How cell clusters are defined in single-cell sequencing data has important consequences for downstream analyses and the interpretation of results, but is often not straightforward. Here, the authors present a new approach that enables the prediction of differentially expressed genes without relying on explicit clustering of cells.