<p>distinct: a method for differential analyses via hierarchical permutation tests, with applications to single-cell data</p>

Simone Tiberi; Helena L. Crowell; Pantelis Samartsidis; Lukas M. Weber; Mark D. Robinson

doi:10.7490/f1000research.1118076.1

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Tiberi S, Crowell HL, Samartsidis P et al. distinct: a method for differential analyses via hierarchical permutation tests, with applications to single-cell data [version 1; not peer reviewed]. F1000Research 2020, 9:754 (poster) (https://doi.org/10.7490/f1000research.1118076.1)

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distinct: a method for differential analyses via hierarchical permutation tests, with applications to single-cell data

Simone Tiberi¹, Helena L. Crowell, Pantelis Samartsidis, Lukas M. Weber, Mark D. Robinson

Published 21 Jul 2020 (https://doi.org/10.7490/f1000research.1118076.1)

Author Affiliations

¹ University of Zurich, Switzerland

Copyright © 2020 Tiberi S 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 21 Jul 2020

distinct: a method for differential analyses via hierarchical permutation tests, with applications to single-cell data
[version 1; not peer reviewed]

Simone Tiberi¹, Helena L. Crowell, Pantelis Samartsidis, Lukas M. Weber, Mark D. Robinson

Author Affiliations

¹ University of Zurich, Switzerland

Presented at

Bioconductor Annual Conference 2020

28th International Conference on Intelligent Systems for Molecular Biology (ISMB) 2020

Abstract

Competing Interests

No competing interests were disclosed

Keywords

Single-cell data, scRNA-seq, Single-cell flow cytometry, Differential analyses, Differential state analyses, Hierarchical permutation tests

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