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Abstract:
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Normalization of RNA-sequencing data is essential for accurate downstream inference, and a number of robust methods exist for bulk RNA-seq experiments. The assumptions upon which bulk methods are based do not hold for single-cell RNA-seq data and, consequently, applying bulk normalization methods in the single-cell setting introduces artifacts that substantially bias downstream analyses. To address this, we introduce SCnorm for accurate and efficient normalization of scRNA-seq data. Applications to a number of data sets demonstrate that SCnorm provides for more accurate estimates of fold-change as well as increased power and precision for downstream analyses.
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