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The contribution of cell cycle to heterogeneity in single-cell RNA-seq data

Nature Biotechnology volume 34, pages 591–593 (2016)Cite this article

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To the Editor:

In the February 2015 issue, Buettner et al.1 reported a computational approach to estimate and remove latent sources of variation, such as cell cycle stage, in gene expression data on single cells. Here we suggest that this variation is largely explained by geometric library size rather than cell cycle stage. Furthermore, we argue that the exogenous spike-ins used by Buettner et al.1 to adjust for technical variation in library preparation and sequencing depth may have led to poorly normalized read counts.

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References

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Authors and Affiliations

  1. Greg Finak and Raphael Gottardo are in the Vaccine and Infectious Disease Division, Andrew McDavid, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.,

    Andrew McDavid, Greg Finak & Raphael Gottardo

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  1. Andrew McDavid
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  2. Greg Finak
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  3. Raphael Gottardo
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Correspondence to Raphael Gottardo.

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Editor's note: This article has been peer reviewed.

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McDavid, A., Finak, G. & Gottardo, R. The contribution of cell cycle to heterogeneity in single-cell RNA-seq data. Nat Biotechnol 34, 591–593 (2016). https://doi.org/10.1038/nbt.3498

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