TY - JOUR
T1 - Single-cell chromatin state analysis with Signac
AU - Stuart, Tim
AU - Srivastava, Avi
AU - Madad, Shaista
AU - Lareau, Caleb A.
AU - Satija, Rahul
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.
PY - 2021/11
Y1 - 2021/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85118443802&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85118443802&partnerID=8YFLogxK
U2 - 10.1038/s41592-021-01282-5
DO - 10.1038/s41592-021-01282-5
M3 - Article
C2 - 34725479
AN - SCOPUS:85118443802
SN - 1548-7091
VL - 18
SP - 1333
EP - 1341
JO - Nature methods
JF - Nature methods
IS - 11
ER -