<p>Deconvolution of transcriptomic data shows biologically and clinically relevant signals in pancreatic tumors</p>

Aliaksandra Kakoichankava; Andrea Bauer; Aliaksandr Siatkouski; Yuri Arlouski; Ivan Zhyltsou; Konstantin Dedyulya; Gunnar Dittmar; Jorg Hoheisel; Petr V. Nazarov

doi:10.7490/f1000research.1117818.1

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Kakoichankava A, Bauer A, Siatkouski A et al. Deconvolution of transcriptomic data shows biologically and clinically relevant signals in pancreatic tumors [version 1; not peer reviewed]. F1000Research 2020, 9:117 (poster) (https://doi.org/10.7490/f1000research.1117818.1)

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Deconvolution of transcriptomic data shows biologically and clinically relevant signals in pancreatic tumors

Aliaksandra Kakoichankava, Andrea Bauer, Aliaksandr Siatkouski, Yuri Arlouski, Ivan Zhyltsou, Konstantin Dedyulya, Gunnar Dittmar, Jorg Hoheisel, Petr V. Nazarov¹

Published 16 Feb 2020 (https://doi.org/10.7490/f1000research.1117818.1)

Author Affiliations

¹ Luxembourg Institute of Health, Luxembourg

Copyright © 2020 Kakoichankava A et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Published 16 Feb 2020

Deconvolution of transcriptomic data shows biologically and clinically relevant signals in pancreatic tumors
[version 1; not peer reviewed]

Aliaksandra Kakoichankava, Andrea Bauer, Aliaksandr Siatkouski, Yuri Arlouski, Ivan Zhyltsou, Konstantin Dedyulya, Gunnar Dittmar, Jorg Hoheisel, Petr V. Nazarov¹

Author Affiliations

¹ Luxembourg Institute of Health, Luxembourg

Presented at

European Bioconductor Meeting 2019

Abstract

Competing Interests

No competing interests were disclosed

Keywords

independent component analysis, deconvolution, pancreatic cancer, survival

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