Integrative analyses of single-cell transcriptome and regulome using MAESTRO.

IF: 17.906

Cited by: 102

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.

Keywords

Spatial Transcriptomics

Gene Expression

Seurat

Cell-type annotation

Computational workflow

Integrate scRNA-seq and scATAC-seq

Predict transcriptional regulators

Single-cell ATAC-seq

Single-cell RNA-seq

MeSH terms

Bone Marrow Cells

Case-Control Studies

Gene Expression Regulation

Humans

Leukemia, Lymphocytic, Chronic, B-Cell

Models, Genetic

Sequence Analysis, RNA

Single-Cell Analysis

Software

Transcriptome

Tumor Microenvironment

Authors

Wang, Chenfei

Sun, Dongqing

Huang, Xin

Wan, Changxin

Li, Ziyi

Han, Ya

Qin, Qian

Fan, Jingyu

Qiu, Xintao

Xie, Yingtian

Meyer, Clifford A

Brown, Myles

Tang, Ming

Long, Henry

Liu, Tao

Liu, X Shirley

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