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Uncertainty in RNA-seq gene expression data

Sonali Arora, Siobhan S. Pattwell, Eric C. Holland, Hamid Bolouri
doi: https://doi.org/10.1101/445601
Sonali Arora
1Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
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Siobhan S. Pattwell
1Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
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Eric C. Holland
1Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
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  • For correspondence: eholland@fhcrc.org hbolouri@fhcrc.org
Hamid Bolouri
1Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
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  • For correspondence: eholland@fhcrc.org hbolouri@fhcrc.org
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Abstract

RNA-sequencing data is widely used to identify disease biomarkers and therapeutic targets. Here, using data from five RNA-seq processing pipelines applied to 6,690 human tumor and normal tissues, we show that for >12% of protein-coding genes, in at least 1% of samples, current best-in-class RNA-seq processing pipelines differ in their abundance estimates by more than four-fold using the same samples and the same set of RNA-seq reads, raising clinical concern.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 18, 2018.
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Uncertainty in RNA-seq gene expression data
Sonali Arora, Siobhan S. Pattwell, Eric C. Holland, Hamid Bolouri
bioRxiv 445601; doi: https://doi.org/10.1101/445601
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Uncertainty in RNA-seq gene expression data
Sonali Arora, Siobhan S. Pattwell, Eric C. Holland, Hamid Bolouri
bioRxiv 445601; doi: https://doi.org/10.1101/445601

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