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powsimR: Power analysis for bulk and single cell RNA-seq experiments

Beate Vieth, View ORCID ProfileChristoph Ziegenhain, View ORCID ProfileSwati Parekh, Wolfgang Enard, Ines Hellmann
doi: https://doi.org/10.1101/117150
Beate Vieth
Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Munich, Germany
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  • For correspondence: vieth@bio.lmu.de
Christoph Ziegenhain
Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Munich, Germany
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  • ORCID record for Christoph Ziegenhain
Swati Parekh
Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Munich, Germany
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Wolfgang Enard
Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Munich, Germany
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Ines Hellmann
Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Munich, Germany
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Abstract

Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes in RNA-seq data. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.

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Posted June 26, 2017.
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powsimR: Power analysis for bulk and single cell RNA-seq experiments
Beate Vieth, Christoph Ziegenhain, Swati Parekh, Wolfgang Enard, Ines Hellmann
bioRxiv 117150; doi: https://doi.org/10.1101/117150
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powsimR: Power analysis for bulk and single cell RNA-seq experiments
Beate Vieth, Christoph Ziegenhain, Swati Parekh, Wolfgang Enard, Ines Hellmann
bioRxiv 117150; doi: https://doi.org/10.1101/117150

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