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SCnorm: A quantile-regression based approach for robust normalization of single-cell RNA-seq data

View ORCID ProfileRhonda Bacher, Li-Fang Chu, Ning Leng, Audrey P. Gasch, James A. Thomson, Ron M. Stewart, Michael Newton, Christina Kendziorski
doi: https://doi.org/10.1101/090167
Rhonda Bacher
1Department of Statistics, University of Wisconsin–Madison, Madison, WI
5Equal contributors
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  • ORCID record for Rhonda Bacher
Li-Fang Chu
2Morgridge Institute for Research, Madison, WI
5Equal contributors
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Ning Leng
2Morgridge Institute for Research, Madison, WI
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Audrey P. Gasch
3Laboratory of Genetics, University of Wisconsin–Madison, Madison, WI
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James A. Thomson
2Morgridge Institute for Research, Madison, WI
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Ron M. Stewart
2Morgridge Institute for Research, Madison, WI
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Michael Newton
1Department of Statistics, University of Wisconsin–Madison, Madison, WI
4Department of Biostatistics and Medical Informatics, University of Wisconsin–Madison, Madison, Wisconsin
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Christina Kendziorski
4Department of Biostatistics and Medical Informatics, University of Wisconsin–Madison, Madison, Wisconsin
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  • For correspondence: kendzior@biostat.wisc.edu
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Summary

Normalization of RNA-sequencing data is essential for accurate downstream inference, but the assumptions upon which most methods are based do not hold in the single-cell setting. Consequently, applying existing normalization methods to single-cell RNA-seq data introduces artifacts that bias downstream analyses. To address this, we introduce SCnorm for accurate and efficient normalization of scRNA-seq data.

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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-NC-ND 4.0 International license.
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Posted November 29, 2016.
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SCnorm: A quantile-regression based approach for robust normalization of single-cell RNA-seq data
Rhonda Bacher, Li-Fang Chu, Ning Leng, Audrey P. Gasch, James A. Thomson, Ron M. Stewart, Michael Newton, Christina Kendziorski
bioRxiv 090167; doi: https://doi.org/10.1101/090167
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SCnorm: A quantile-regression based approach for robust normalization of single-cell RNA-seq data
Rhonda Bacher, Li-Fang Chu, Ning Leng, Audrey P. Gasch, James A. Thomson, Ron M. Stewart, Michael Newton, Christina Kendziorski
bioRxiv 090167; doi: https://doi.org/10.1101/090167

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