<p>Interactions between explicit and latent covariates detect cell-type specific treatment effects in exploratory single cell analysis without clustering</p>

Constantin Ahlmann-Eltze; Wolfgang Huber

doi:10.7490/f1000research.1118442.1

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Ahlmann-Eltze C and Huber W. Interactions between explicit and latent covariates detect cell-type specific treatment effects in exploratory single cell analysis without clustering [version 1; not peer reviewed]. F1000Research 2020, 9:1453 (poster) (https://doi.org/10.7490/f1000research.1118442.1)

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Interactions between explicit and latent covariates detect cell-type specific treatment effects in exploratory single cell analysis without clustering

Constantin Ahlmann-Eltze¹, Wolfgang Huber

Published 14 Dec 2020 (https://doi.org/10.7490/f1000research.1118442.1)

Author Affiliations

¹ European Molecular Biology Laboratory, Germany

Copyright © 2020 Ahlmann-Eltze C and Huber W. 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 14 Dec 2020

Interactions between explicit and latent covariates detect cell-type specific treatment effects in exploratory single cell analysis without clustering
[version 1; not peer reviewed]

Constantin Ahlmann-Eltze¹, Wolfgang Huber

Author Affiliations

¹ European Molecular Biology Laboratory, Germany

Presented at

European Bioconductor Meeting 2020

Abstract

Competing Interests

No competing interests were disclosed

Keywords

single cell, statistical model, linear model, dimensionality reduction

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