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Normalizing single-cell RNA sequencing data: challenges and opportunities


Single-cell transcriptomics is becoming an important component of the molecular biologist's toolkit. A critical step when analyzing data generated using this technology is normalization. However, normalization is typically performed using methods developed for bulk RNA sequencing or even microarray data, and the suitability of these methods for single-cell transcriptomics has not been assessed. We here discuss commonly used normalization approaches and illustrate how these can produce misleading results. Finally, we present alternative approaches and provide recommendations for single-cell RNA sequencing users.

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Figure 1: Cell- and gene-specific effects in RNA-seq experiments.
Figure 2: Comparison of bulk-based normalization methods in real and simulated data sets.
Figure 3: ERCC spike-ins can be used to estimate mRNA content.


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We thank several members of the Marioni laboratory (European Molecular Biology Laboratory - European Bioinformatics Institute, EMBL-EBI; Cancer Research UK - Cambridge Institute, CRUK-CI) for support and discussions throughout the preparation of this manuscript. In particular, we are grateful to A. Lun (CRUK-CI) for constructive comments on an earlier version of the manuscript. We are also grateful to UC Berkeley collaborator J. Ngai and his group members. C.A.V., A.S., and J.C.M. acknowledge core EMBL funding. C.A.V. was supported by core MRC funding (MRC MC UP 0801/1) and by The Alan Turing Institute under the EPSRC grant no. EP/N510129/1. J.C.M. acknowledges core support from CRUK. A.S. acknowledges funding from the Wellcome Trust Strategic Award 105031/D/14/Z, “Tracing early mammalian lineage decisions by single-cell genomics.” D.R. and S.D. are supported by the US National Institutes of Health BRAIN Initiative grant no. U01 MH105979 (PI, J. Ngai).

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C.A.V., D.R., and A.S. performed analyses. C.A.V., D.R., A.S., S.D., and J.C.M. wrote the manuscript. S.D. and J.C.M. supervised the study.

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Correspondence to Sandrine Dudoit or John C Marioni.

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The authors declare no competing financial interests.

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Vallejos, C., Risso, D., Scialdone, A. et al. Normalizing single-cell RNA sequencing data: challenges and opportunities. Nat Methods 14, 565–571 (2017).

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