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A clustering-independent method for finding differentially expressed genes in single-cell transcriptome data
oleh: Alexis Vandenbon, Diego Diez
Format: | Article |
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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.