IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v6y2015i1d10.1038_ncomms9687.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms9687
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms9687?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.
    3. Hyun Kim & Won Chang & Seok Joo Chae & Jong-Eun Park & Minseok Seo & Jae Kyoung Kim, 2024. "scLENS: data-driven signal detection for unbiased scRNA-seq data analysis," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms9687. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.