https://doi.org/10.7490/f1000research.1118270.1
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Chepeleva M, Kakoichankava A, Muller A et al. Simultaneous deconvolution of bulk-sample and single-cell data leads to improved characterization of tumors [version 1; not peer reviewed]. F1000Research 2020, 9(ISCB Comm J):1025 (slides) (https://doi.org/10.7490/f1000research.1118270.1)
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Simultaneous deconvolution of bulk-sample and single-cell data leads to improved characterization of tumors

Maryna Chepeleva1, Aliaksandra Kakoichankava, Arnaud Muller, Tony Kaoma, Mikalai M. Yatskou, Petr V. Nazarov2
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Published 22 Aug 2020

Simultaneous deconvolution of bulk-sample and single-cell data leads to improved characterization of tumors

[version 1; not peer reviewed]

Maryna Chepeleva1, Aliaksandra Kakoichankava, Arnaud Muller, Tony Kaoma, Mikalai M. Yatskou, Petr V. Nazarov2
Author Affiliations
1 Belarusian State University, Belarus
2 Luxembourg Institute of Health, Luxembourg
Presented at
28th International Conference on Intelligent Systems for Molecular Biology (ISMB) 2020
Abstract
Competing Interests

No competing interests were disclosed

Keywords
transcriptomics, RNA-seq, independent component analysis, deconvolution, cancer, single-cell, survival
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