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Multimodal single-cell chromatin analysis with Signac

View ORCID ProfileTim Stuart, View ORCID ProfileAvi Srivastava, View ORCID ProfileCaleb Lareau, View ORCID ProfileRahul Satija
doi: https://doi.org/10.1101/2020.11.09.373613
Tim Stuart
1New York Genome Center, New York City, NY
2Center for Genomics and Systems Biology, New York University, New York City, NY
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  • For correspondence: tstuart@nygenome.org rsatija@nygenome.org
Avi Srivastava
1New York Genome Center, New York City, NY
2Center for Genomics and Systems Biology, New York University, New York City, NY
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Caleb Lareau
4Department of Genetics and Pathology, Stanford University, Stanford, CA
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Rahul Satija
1New York Genome Center, New York City, NY
2Center for Genomics and Systems Biology, New York University, New York City, NY
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  • For correspondence: tstuart@nygenome.org rsatija@nygenome.org
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Abstract

The recent development of experimental methods for measuring chromatin state at single-cell resolution has created a need for computational tools capable of analyzing these datasets. Here we developed Signac, a framework for the analysis of single-cell chromatin data, as an extension of the Seurat R toolkit for single-cell multimodal analysis. Signac enables an end-to-end analysis of single-cell chromatin data, including peak calling, quantification, quality control, dimension reduction, clustering, integration with single-cell gene expression datasets, DNA motif analysis, and interactive visualization. Furthermore, Signac facilitates the analysis of multimodal single-cell chromatin data, including datasets that co-assay DNA accessibility with gene expression, protein abundance, and mitochondrial genotype. We demonstrate scaling of the Signac framework to datasets containing over 700,000 cells.

Availability Installation instructions, documentation, and tutorials are available at: https://satijalab.org/signac/

Competing Interest Statement

In the past three years, RS has worked as a consultant for Bristol-Myers Squibb, Regeneron, and Kallyope, and served as an SAB member for ImmunAI and Apollo Life Sciences GmbH.

Footnotes

  • https://github.com/timoast/signac/

  • https://satijalab.org/signac/

  • https://cran.r-project.org/package=Signac

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted November 10, 2020.
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Multimodal single-cell chromatin analysis with Signac
Tim Stuart, Avi Srivastava, Caleb Lareau, Rahul Satija
bioRxiv 2020.11.09.373613; doi: https://doi.org/10.1101/2020.11.09.373613
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Multimodal single-cell chromatin analysis with Signac
Tim Stuart, Avi Srivastava, Caleb Lareau, Rahul Satija
bioRxiv 2020.11.09.373613; doi: https://doi.org/10.1101/2020.11.09.373613

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