Publication | Open Access
Multimodal single-cell chromatin analysis with Signac
162
Citations
69
References
2020
Year
Unknown Venue
Chromatin StateMolecular BiologyGene Expression ProfilingEpigeneticsTrajectory AnalysisSingle Cell SequencingSignac FrameworkDimension ReductionSingle-cell GenomicsOmicsGene ExpressionSingle-cell AnalysisBioinformaticsCell BiologyFunctional GenomicsChromatinChromatin StructureChromatin RemodelingNatural SciencesComputational BiologySystems BiologyMedicine
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/
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