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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
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  • For correspondence: alexisvdb@infront.kyoto-u.ac.jp
Diego Diez
3Immunology Frontier Research Center, Osaka University, Japan
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Posted November 08, 2019.
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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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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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