<p>Calling variants from RNA-Seq data identifies significant eQTLs in a small cohort of asthma patients</p>

Artika P. Nath; Milica Ng; Judith Field; Nicholas J. Wilson; Michael J. Wilson; Michael Inouye; Monther Alhamdoosh

doi:10.7490/f1000research.1115068.1

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Nath AP, Ng M, Field J et al. Calling variants from RNA-Seq data identifies significant eQTLs in a small cohort of asthma patients [version 1; not peer reviewed]. F1000Research 2017, 6:2002 (poster) (https://doi.org/10.7490/f1000research.1115068.1)

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Calling variants from RNA-Seq data identifies significant eQTLs in a small cohort of asthma patients

Artika P. Nath¹, Milica Ng, Judith Field, Nicholas J. Wilson, Michael J. Wilson, Michael Inouye¹, Monther Alhamdoosh²

Published 13 Nov 2017 (https://doi.org/10.7490/f1000research.1115068.1)

Author Affiliations

¹ Baker Heart and Diabetes Institute, Australia
² CSL Limited, Australia

Copyright © 2017 Nath AP 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 13 Nov 2017

Calling variants from RNA-Seq data identifies significant eQTLs in a small cohort of asthma patients
[version 1; not peer reviewed]

Artika P. Nath¹, Milica Ng, Judith Field, Nicholas J. Wilson, Michael J. Wilson, Michael Inouye¹, Monther Alhamdoosh²

Author Affiliations

¹ Baker Heart and Diabetes Institute, Australia
² CSL Limited, Australia

Presented at

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

Abstract

Competing Interests

MN, JF, NJW, MJW, and MA are employees of CSL Limited.

Keywords

RNA-seq, variant calling, asthma, patients, eQTL, imputation

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