Genome Biology (Aug 2020)

Integrative analyses of single-cell transcriptome and regulome using MAESTRO

  • Chenfei Wang,
  • Dongqing Sun,
  • Xin Huang,
  • Changxin Wan,
  • Ziyi Li,
  • Ya Han,
  • Qian Qin,
  • Jingyu Fan,
  • Xintao Qiu,
  • Yingtian Xie,
  • Clifford A. Meyer,
  • Myles Brown,
  • Ming Tang,
  • Henry Long,
  • Tao Liu,
  • X. Shirley Liu

DOI
https://doi.org/10.1186/s13059-020-02116-x
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 28

Abstract

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Abstract We present Model-based AnalysEs of Transcriptome and RegulOme (MAESTRO), a comprehensive open-source computational workflow ( http://github.com/liulab-dfci/MAESTRO ) for the integrative analyses of single-cell RNA-seq (scRNA-seq) and ATAC-seq (scATAC-seq) data from multiple platforms. MAESTRO provides functions for pre-processing, alignment, quality control, expression and chromatin accessibility quantification, clustering, differential analysis, and annotation. By modeling gene regulatory potential from chromatin accessibilities at the single-cell level, MAESTRO outperforms the existing methods for integrating the cell clusters between scRNA-seq and scATAC-seq. Furthermore, MAESTRO supports automatic cell-type annotation using predefined cell type marker genes and identifies driver regulators from differential scRNA-seq genes and scATAC-seq peaks.

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