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Strength in numbers from integrated single-cell neuroscience

Nature Biotechnology volume 36, pages 41–42 (2018)Cite this article

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An Erratum to this article was published on 01 October 2018

This article has been updated

Combining epigenomics and transcriptomics data from human brain samples reveals regulatory mechanisms that underlie cell type identity.

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Figure 1: Schematic of integrated single cell analysis of the human brain.

Change history

  • 07 August 2018

    In the version of this article initially published, the sentence fragment "The scNuc-seq approach is complementary to the recently published massively parallel" preceding "The sNuc-seq approach is complementary to the recently published DroNc-seq method" should have been deleted. The error has been corrected in the HTML and PDF versions of the article.

  • 01 October 2018

    Nat. Biotechnol. 36, 41–42 (2018); published online 10 January 2018; corrected after print 7 August 2018 In the version of this article initially published, the sentence fragment “The scNuc-seq approach is complementary to the recently published massively parallel” preceding “The sNuc-seq approach is complementary to the recently published DroNc-seq method” should have been deleted.

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Authors and Affiliations

  1. Rahul Satija is at the New York Genome Center, New York, New York, USA, and New York University, Center for Genomics and Systems Biology, New York, New York, USA.,

    Rahul Satija

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  1. Rahul Satija
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Correspondence to Rahul Satija.

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Satija, R. Strength in numbers from integrated single-cell neuroscience. Nat Biotechnol 36, 41–42 (2018). https://doi.org/10.1038/nbt.4055

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