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singleCellHaystack: A clustering-independent method for finding differentially expressed genes in single-cell transcriptome data
Alexis Vandenbon, View ORCID ProfileDiego Diez
doi: https://doi.org/10.1101/557967
Alexis Vandenbon
1Institute for Frontier Life and Medical Sciences, Kyoto University, Japan
2Institute for Liberal Arts and Sciences, Kyoto University, Japan
Diego Diez
3Immunology Frontier Research Center, Osaka University, Japan
Posted November 08, 2019.
singleCellHaystack: A clustering-independent method for finding differentially expressed genes in single-cell transcriptome data
Alexis Vandenbon, Diego Diez
bioRxiv 557967; doi: https://doi.org/10.1101/557967
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