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Inference and effects of barcode multiplets in droplet-based single-cell assays

Author

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  • Caleb A. Lareau

    (Harvard University
    Broad Institute of MIT and Harvard
    Harvard Medical School)

  • Sai Ma

    (Harvard University
    Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology)

  • Fabiana M. Duarte

    (Harvard University
    Broad Institute of MIT and Harvard)

  • Jason D. Buenrostro

    (Harvard University
    Broad Institute of MIT and Harvard)

Abstract

A widespread assumption for single-cell analyses specifies that one cell’s nucleic acids are predominantly captured by one oligonucleotide barcode. Here, we show that ~13–21% of cell barcodes from the 10x Chromium scATAC-seq assay may have been derived from a droplet with more than one oligonucleotide sequence, which we call “barcode multiplets”. We demonstrate that barcode multiplets can be derived from at least two different sources. First, we confirm that approximately 4% of droplets from the 10x platform may contain multiple beads. Additionally, we find that approximately 5% of beads may contain detectable levels of multiple oligonucleotide barcodes. We show that this artifact can confound single-cell analyses, including the interpretation of clonal diversity and proliferation of intra-tumor lymphocytes. Overall, our work provides a conceptual and computational framework to identify and assess the impacts of barcode multiplets in single-cell data.

Suggested Citation

  • Caleb A. Lareau & Sai Ma & Fabiana M. Duarte & Jason D. Buenrostro, 2020. "Inference and effects of barcode multiplets in droplet-based single-cell assays," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14667-5
    DOI: 10.1038/s41467-020-14667-5
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    Cited by:

    1. Junhao Li & Manoj K. Jaiswal & Jo-Fan Chien & Alexey Kozlenkov & Jinyoung Jung & Ping Zhou & Mahammad Gardashli & Luc J. Pregent & Erica Engelberg-Cook & Dennis W. Dickson & Veronique V. Belzil & Eran, 2023. "Divergent single cell transcriptome and epigenome alterations in ALS and FTD patients with C9orf72 mutation," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    2. Zhu, Guang & Lin, Zhenhua, 2021. "Commentary on statistical mechanical models of cancer," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).

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