henhao
Sign in
GenomicsNature Methods
Peer-reviewed journal article

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

Rhonda L. BacheriD, Li‐Fang ChuiD, Ning LengiD, Audrey P. GaschiD, James Alexander ThomsoniD, Ron M. StewartiD, Michael A. NewtoniD, Christina M. KendziorskiiD

PDFDOIPreprint

Abstract

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.

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISBorella '21Cole '19Townes '20Hafemeister '19McCarthy '16Ding '16
76% semantic matchBioinformatics
Matteo Borella, Graziano Martello, Davide Risso+1 more·Bioinformatics·Sep 8, 2021· 19 citations