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

Nature Biotechnology volume 34, pages 593–595 (2016)Cite this article

Buettner, Marioni and Stegle reply:

McDavid et al.1 raise several interesting points regarding our method to account for heterogeneity in single-cell gene expression. They argue that it is geometric library size and not cell cycle effects that explains the majority of the variation we observe in our RNA sequencing data. They also highlight challenges in using ERCC spike-ins for normalizing sequencing read counts. We agree that the normalization of single-cell RNA-seq data is an important issue that requires careful attention and have acknowledged previous papers highlighting these issues2,3 . However, we contend that many of the points raised by McDavid et al. were discussed in our original manuscript. Additionally, we disagree with several aspects of their interpretation and analysis.

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Figure 1: Correlation of alternative estimates of size factors in comparison to the cell cycle factor estimated by scLVM.
Figure 3: Visualization of the T-cells using a diffusion map approach.
Figure 2: Inter-gene correlation coefficients for genes in gene sets identified by CAMERA and topGO.

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Authors and Affiliations

  1. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

    Andrew McDavid, Greg Finak & Raphael Gottardo

Authors
  1. Andrew McDavid
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  2. Greg Finak
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  3. Raphael Gottardo
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Corresponding author

Correspondence to Raphael Gottardo.

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The author declare no competing financial interests.

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

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McDavid, A., Finak, G. & Gottardo, R. Reply to The contribution of cell cycle to heterogeneity in single-cell RNA-seq data. Nat Biotechnol 34, 593–595 (2016). https://doi.org/10.1038/nbt.3607

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