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 comprehensive toolkit for the analysis of single-cell chromatin data. 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. Through its seamless compatibility with the Seurat package, Signac facilitates the analysis of diverse 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 analyze datasets containing over 700,000 cells.

Keywords

ChromatinComputational biologyComputer scienceState (computer science)Cell biologyChemistryBiologyGeneticsDNAAlgorithm

MeSH Terms

Bone Marrow CellsChromatinComputational BiologyGene Expression ProfilingHumansLeukocytesMononuclearMitochondriaSequence AnalysisDNASingle-Cell AnalysisSoftware

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Publication Info

Year
2021
Type
article
Volume
18
Issue
11
Pages
1333-1341
Citations
1536
Access
Closed

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1536
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Cite This

Tim Stuart, Avi Srivastava, Shaista Madad et al. (2021). Single-cell chromatin state analysis with Signac. Nature Methods , 18 (11) , 1333-1341. https://doi.org/10.1038/s41592-021-01282-5

Identifiers

DOI
10.1038/s41592-021-01282-5
PMID
34725479
PMCID
PMC9255697

Data Quality

Data completeness: 90%