<p>Annotating single-cell RNAseq clusters by similarity to reference single-cell datasets</p>

Sarah Williams; Sonika Tyagi; David Powell

doi:10.7490/f1000research.1115101.1

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Williams S, Tyagi S and Powell D. Annotating single-cell RNAseq clusters by similarity to reference single-cell datasets [version 1; not peer reviewed]. F1000Research 2017, 6:2047 (poster) (https://doi.org/10.7490/f1000research.1115101.1)

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Annotating single-cell RNAseq clusters by similarity to reference single-cell datasets

Sarah Williams¹, Sonika Tyagi, David Powell

Published 24 Nov 2017 (https://doi.org/10.7490/f1000research.1115101.1)

Author Affiliations

¹ Monash University, Australia

Copyright © 2017 Williams 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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CITE

Published 24 Nov 2017

Annotating single-cell RNAseq clusters by similarity to reference single-cell datasets
[version 1; not peer reviewed]

Sarah Williams¹, Sonika Tyagi, David Powell

Author Affiliations

¹ Monash University, Australia

Presented at

Australian Bioinformatics & Computational Biology Society (ABACBS) Annual Conference 2017

Abstract

Competing Interests

No competing interests were disclosed

Keywords

scRNAseq, single cell RNAseq, RNAseq, tools

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