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MarcoPolo: a clustering-free approach to the exploration of differentially expressed genes along with group information in single-cell RNA-seq data

Chanwoo Kim, Hanbin Lee, Juhee Jeong, Keehoon Jung, View ORCID ProfileBuhm Han
doi: https://doi.org/10.1101/2020.11.23.393900
Chanwoo Kim
1Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
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Hanbin Lee
2Department of Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
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Juhee Jeong
3Department of Biomedical Sciences, BK21 Plus Biomedical Science Project, Seoul National University College of Medicine, Seoul, Republic of Korea
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Keehoon Jung
3Department of Biomedical Sciences, BK21 Plus Biomedical Science Project, Seoul National University College of Medicine, Seoul, Republic of Korea
4Department of Anatomy and Cell Biology, Seoul National University College of Medicine, Seoul, Republic of Korea
5Institute of Allergy and Clinical Immunology, Seoul National University Medical Research Center, Seoul, Republic of Korea
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Buhm Han
3Department of Biomedical Sciences, BK21 Plus Biomedical Science Project, Seoul National University College of Medicine, Seoul, Republic of Korea
6Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, Republic of Korea
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  • ORCID record for Buhm Han
  • For correspondence: buhm.han@snu.ac.kr
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  • https://github.com/ch6845/MarcoPolo

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Posted January 12, 2021.
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MarcoPolo: a clustering-free approach to the exploration of differentially expressed genes along with group information in single-cell RNA-seq data
Chanwoo Kim, Hanbin Lee, Juhee Jeong, Keehoon Jung, Buhm Han
bioRxiv 2020.11.23.393900; doi: https://doi.org/10.1101/2020.11.23.393900
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MarcoPolo: a clustering-free approach to the exploration of differentially expressed genes along with group information in single-cell RNA-seq data
Chanwoo Kim, Hanbin Lee, Juhee Jeong, Keehoon Jung, Buhm Han
bioRxiv 2020.11.23.393900; doi: https://doi.org/10.1101/2020.11.23.393900

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