Exponential scaling of single-cell RNA-seq in the past decade

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Abstract

Measurement of the transcriptomes of single cells has been feasible for only a few years, but it has become an extremely popular assay. While many types of analysis can be carried out and various questions can be answered by single-cell RNA-seq, a central focus is the ability to survey the diversity of cell types in a sample. Unbiased and reproducible cataloging of gene expression patterns in distinct cell types requires large numbers of cells. Technological developments and protocol improvements have fueled consistent and exponential increases in the number of cells that can be studied in single-cell RNA-seq analyses. In this Perspective, we highlight the key technological developments that have enabled this growth in the data obtained from single-cell RNA-seq experiments.

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Figure 1: Scaling of scRNA-seq experiments.

Change history

  • 22 March 2018

    In the version of this article initially published, the sentence "This method was also used for MARS-seq (massively parallel scRNA-seq)33, and later for InDrop (droplet sequencing)34 and Seq-Well (a well-array-based variation on MARS-seq)35" was incorrect. The words "and Seq-Well (a well-array-based variation on MARS-seq)35" should have been deleted. This error has been corrected in the HTML and PDF versions of the article. In addition, refs. 36–41 in the original paper have been renumbered as 35–40 and original ref. 35 has been renumbered as ref. 41 throughout the text and in Figure 1.

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Acknowledgements

We thank Z.-S. Chong, K.N. Natarajan, T. Gomes, N. Edner and K. Meyer for reading the manuscript and giving helpful feedback. R.V.-T. is supported by an EMBO Long-Term Fellowship and a Human Frontier Science Program Long-Term Fellowship.

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V.S., R.V.-T. and S.A.T. wrote the manuscript. V.S. prepared Figure 1.

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Correspondence to Valentine Svensson or Sarah A Teichmann.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Table 1

Sample sizes from representative scRNA-seq studies. This table details the number of single cells reported in selected scRNA-seq studies from the literature where increases in scale or particularly large data sets are mentioned. Also indicated are the protocols used and the cell isolation strategies. (XLSX 12 kb)

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Svensson, V., Vento-Tormo, R. & Teichmann, S. Exponential scaling of single-cell RNA-seq in the past decade. Nat Protoc 13, 599–604 (2018). https://doi.org/10.1038/nprot.2017.149

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