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SCHNEL: Scalable clustering of high dimensional single-cell data
View ORCID ProfileTamim Abdelaal, Paul de Raadt, View ORCID ProfileBoudewijn P.F. Lelieveldt, View ORCID ProfileMarcel J.T. Reinders, View ORCID ProfileAhmed Mahfouz
doi: https://doi.org/10.1101/2020.03.30.015925
Tamim Abdelaal
1Delft Bioinformatics Lab, Delft University of Technology, 2628 XE Delft, The Netherlands
2Leiden Computational Biology Center, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
Paul de Raadt
2Leiden Computational Biology Center, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
Boudewijn P.F. Lelieveldt
1Delft Bioinformatics Lab, Delft University of Technology, 2628 XE Delft, The Netherlands
2Leiden Computational Biology Center, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
Marcel J.T. Reinders
1Delft Bioinformatics Lab, Delft University of Technology, 2628 XE Delft, The Netherlands
2Leiden Computational Biology Center, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
3Department of Human Genetics, Leiden University Medical Center, Leiden 2333ZC, The Netherlands
Ahmed Mahfouz
1Delft Bioinformatics Lab, Delft University of Technology, 2628 XE Delft, The Netherlands
2Leiden Computational Biology Center, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
3Department of Human Genetics, Leiden University Medical Center, Leiden 2333ZC, The Netherlands

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Posted March 31, 2020.
SCHNEL: Scalable clustering of high dimensional single-cell data
Tamim Abdelaal, Paul de Raadt, Boudewijn P.F. Lelieveldt, Marcel J.T. Reinders, Ahmed Mahfouz
bioRxiv 2020.03.30.015925; doi: https://doi.org/10.1101/2020.03.30.015925
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