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Integrative analyses of single-cell transcriptome and regulome using MAESTRO

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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412809/
https://www.ncbi.nlm.nih.gov/pubmed/32767996
http://dx.doi.org/10.1186/s13059-020-02116-x
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author 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
author_facet 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
author_sort Wang, Chenfei
collection PubMed
description 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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spelling pubmed-74128092020-08-10 Integrative analyses of single-cell transcriptome and regulome using MAESTRO 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 Genome Biol Software 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. BioMed Central 2020-08-07 /pmc/articles/PMC7412809/ /pubmed/32767996 http://dx.doi.org/10.1186/s13059-020-02116-x Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
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
Integrative analyses of single-cell transcriptome and regulome using MAESTRO
title Integrative analyses of single-cell transcriptome and regulome using MAESTRO
title_full Integrative analyses of single-cell transcriptome and regulome using MAESTRO
title_fullStr Integrative analyses of single-cell transcriptome and regulome using MAESTRO
title_full_unstemmed Integrative analyses of single-cell transcriptome and regulome using MAESTRO
title_short Integrative analyses of single-cell transcriptome and regulome using MAESTRO
title_sort integrative analyses of single-cell transcriptome and regulome using maestro
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412809/
https://www.ncbi.nlm.nih.gov/pubmed/32767996
http://dx.doi.org/10.1186/s13059-020-02116-x
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