<p>Power analysis of cell-type deconvolution across human tissues</p>

Anna Vathrakokoili Pournara; Zhichao  Miao; Ozgur Yilmaz  Beker; Irene  Papatheodorou

doi:10.7490/f1000research.1119339.1

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Vathrakokoili Pournara A, Miao Z, Beker OY and Papatheodorou I. Power analysis of cell-type deconvolution across human tissues [version 1; not peer reviewed]. F1000Research 2022, 11:1585 (slides) (https://doi.org/10.7490/f1000research.1119339.1)

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Power analysis of cell-type deconvolution across human tissues

Anna Vathrakokoili Pournara¹, Zhichao Miao, Ozgur Yilmaz Beker, Irene Papatheodorou

Published 26 Dec 2022 (https://doi.org/10.7490/f1000research.1119339.1)

Author Affiliations

¹ EMBL European Bioinformatics Institute, UK

Copyright © 2022 Vathrakokoili Pournara 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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CITE

Published 26 Dec 2022

Power analysis of cell-type deconvolution across human tissues
[version 1; not peer reviewed]

Anna Vathrakokoili Pournara¹, Zhichao Miao, Ozgur Yilmaz Beker, Irene Papatheodorou

Author Affiliations

¹ EMBL European Bioinformatics Institute, UK

Presented at

European Conference on Computational Biology (ECCB) 2022

Abstract

Competing Interests

No competing interests were disclosed

Keywords

deconvolution, cell proportions, benchmarking, bulk samples, single-cell RNA-sequencing, batch effects

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