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Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression

Author

Listed:
  • Jong Kyoung Kim

    (European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus)

  • Aleksandra A. Kolodziejczyk

    (European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus
    Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus)

  • Tomislav Ilicic

    (European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus
    Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus)

  • Sarah A. Teichmann

    (European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus
    Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus)

  • John C. Marioni

    (European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus
    Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus)

Abstract

Single-cell RNA-sequencing (scRNA-seq) facilitates identification of new cell types and gene regulatory networks as well as dissection of the kinetics of gene expression and patterns of allele-specific expression. However, to facilitate such analyses, separating biological variability from the high level of technical noise that affects scRNA-seq protocols is vital. Here we describe and validate a generative statistical model that accurately quantifies technical noise with the help of external RNA spike-ins. Applying our approach to investigate stochastic allele-specific expression in individual cells, we demonstrate that a large fraction of stochastic allele-specific expression can be explained by technical noise, especially for lowly and moderately expressed genes: we predict that only 17.8% of stochastic allele-specific expression patterns are attributable to biological noise with the remainder due to technical noise.

Suggested Citation

  • Jong Kyoung Kim & Aleksandra A. Kolodziejczyk & Tomislav Ilicic & Sarah A. Teichmann & John C. Marioni, 2015. "Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression," Nature Communications, Nature, vol. 6(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms9687
    DOI: 10.1038/ncomms9687
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    Cited by:

    1. Hyeon-Jin Kim & Greg Booth & Lauren Saunders & Sanjay Srivatsan & José L. McFaline-Figueroa & Cole Trapnell, 2022. "Nuclear oligo hashing improves differential analysis of single-cell RNA-seq," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Lingfei Wang, 2021. "Single-cell normalization and association testing unifying CRISPR screen and gene co-expression analyses with Normalisr," Nature Communications, Nature, vol. 12(1), pages 1-13, December.

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