Integrative analyses of single-cell transcriptome and regulome using MAESTRO

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

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Single-cell RNA-seq Single-cell ATAC-seq Computational workflow Integrate scRNA-seq and scATAC-seq Cell-type annotation Predict transcriptional regulators

Übergeordnetes Werk:	Enthalten in: Genome biology - London : BioMed Central, 2000, 21(2020), 1 vom: 07. Aug.
Übergeordnetes Werk:	volume:21 ; year:2020 ; number:1 ; day:07 ; month:08

Links:	Volltext

DOI / URN:	10.1186/s13059-020-02116-x

Katalog-ID:	SPR040592529

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author_variant	c w cw d s ds x h xh c w cw z l zl y h yh q q qq j f jf x q xq y x yx c a m ca cam m b mb m t mt h l hl t l tl x s l xs xsl
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allfields	10.1186/s13059-020-02116-x doi (DE-627)SPR040592529 (SPR)s13059-020-02116-x-e DE-627 ger DE-627 rakwb eng 570 ASE 42.13 bkl 42.20 bkl Wang, Chenfei verfasserin aut Integrative analyses of single-cell transcriptome and regulome using MAESTRO 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Single-cell RNA-seq (dpeaa)DE-He213 Single-cell ATAC-seq (dpeaa)DE-He213 Computational workflow (dpeaa)DE-He213 Integrate scRNA-seq and scATAC-seq (dpeaa)DE-He213 Cell-type annotation (dpeaa)DE-He213 Predict transcriptional regulators (dpeaa)DE-He213 Sun, Dongqing verfasserin aut Huang, Xin verfasserin aut Wan, Changxin verfasserin aut Li, Ziyi verfasserin aut Han, Ya verfasserin aut Qin, Qian verfasserin aut Fan, Jingyu verfasserin aut Qiu, Xintao verfasserin aut Xie, Yingtian verfasserin aut Meyer, Clifford A. verfasserin aut Brown, Myles verfasserin aut Tang, Ming verfasserin aut Long, Henry verfasserin aut Liu, Tao verfasserin aut Liu, X. Shirley verfasserin aut Enthalten in Genome biology London : BioMed Central, 2000 21(2020), 1 vom: 07. Aug. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:21 year:2020 number:1 day:07 month:08 https://dx.doi.org/10.1186/s13059-020-02116-x kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.13 ASE 42.20 ASE AR 21 2020 1 07 08
spelling	10.1186/s13059-020-02116-x doi (DE-627)SPR040592529 (SPR)s13059-020-02116-x-e DE-627 ger DE-627 rakwb eng 570 ASE 42.13 bkl 42.20 bkl Wang, Chenfei verfasserin aut Integrative analyses of single-cell transcriptome and regulome using MAESTRO 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Single-cell RNA-seq (dpeaa)DE-He213 Single-cell ATAC-seq (dpeaa)DE-He213 Computational workflow (dpeaa)DE-He213 Integrate scRNA-seq and scATAC-seq (dpeaa)DE-He213 Cell-type annotation (dpeaa)DE-He213 Predict transcriptional regulators (dpeaa)DE-He213 Sun, Dongqing verfasserin aut Huang, Xin verfasserin aut Wan, Changxin verfasserin aut Li, Ziyi verfasserin aut Han, Ya verfasserin aut Qin, Qian verfasserin aut Fan, Jingyu verfasserin aut Qiu, Xintao verfasserin aut Xie, Yingtian verfasserin aut Meyer, Clifford A. verfasserin aut Brown, Myles verfasserin aut Tang, Ming verfasserin aut Long, Henry verfasserin aut Liu, Tao verfasserin aut Liu, X. Shirley verfasserin aut Enthalten in Genome biology London : BioMed Central, 2000 21(2020), 1 vom: 07. Aug. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:21 year:2020 number:1 day:07 month:08 https://dx.doi.org/10.1186/s13059-020-02116-x kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.13 ASE 42.20 ASE AR 21 2020 1 07 08
allfields_unstemmed	10.1186/s13059-020-02116-x doi (DE-627)SPR040592529 (SPR)s13059-020-02116-x-e DE-627 ger DE-627 rakwb eng 570 ASE 42.13 bkl 42.20 bkl Wang, Chenfei verfasserin aut Integrative analyses of single-cell transcriptome and regulome using MAESTRO 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Single-cell RNA-seq (dpeaa)DE-He213 Single-cell ATAC-seq (dpeaa)DE-He213 Computational workflow (dpeaa)DE-He213 Integrate scRNA-seq and scATAC-seq (dpeaa)DE-He213 Cell-type annotation (dpeaa)DE-He213 Predict transcriptional regulators (dpeaa)DE-He213 Sun, Dongqing verfasserin aut Huang, Xin verfasserin aut Wan, Changxin verfasserin aut Li, Ziyi verfasserin aut Han, Ya verfasserin aut Qin, Qian verfasserin aut Fan, Jingyu verfasserin aut Qiu, Xintao verfasserin aut Xie, Yingtian verfasserin aut Meyer, Clifford A. verfasserin aut Brown, Myles verfasserin aut Tang, Ming verfasserin aut Long, Henry verfasserin aut Liu, Tao verfasserin aut Liu, X. Shirley verfasserin aut Enthalten in Genome biology London : BioMed Central, 2000 21(2020), 1 vom: 07. Aug. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:21 year:2020 number:1 day:07 month:08 https://dx.doi.org/10.1186/s13059-020-02116-x kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.13 ASE 42.20 ASE AR 21 2020 1 07 08
allfieldsGer	10.1186/s13059-020-02116-x doi (DE-627)SPR040592529 (SPR)s13059-020-02116-x-e DE-627 ger DE-627 rakwb eng 570 ASE 42.13 bkl 42.20 bkl Wang, Chenfei verfasserin aut Integrative analyses of single-cell transcriptome and regulome using MAESTRO 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Single-cell RNA-seq (dpeaa)DE-He213 Single-cell ATAC-seq (dpeaa)DE-He213 Computational workflow (dpeaa)DE-He213 Integrate scRNA-seq and scATAC-seq (dpeaa)DE-He213 Cell-type annotation (dpeaa)DE-He213 Predict transcriptional regulators (dpeaa)DE-He213 Sun, Dongqing verfasserin aut Huang, Xin verfasserin aut Wan, Changxin verfasserin aut Li, Ziyi verfasserin aut Han, Ya verfasserin aut Qin, Qian verfasserin aut Fan, Jingyu verfasserin aut Qiu, Xintao verfasserin aut Xie, Yingtian verfasserin aut Meyer, Clifford A. verfasserin aut Brown, Myles verfasserin aut Tang, Ming verfasserin aut Long, Henry verfasserin aut Liu, Tao verfasserin aut Liu, X. Shirley verfasserin aut Enthalten in Genome biology London : BioMed Central, 2000 21(2020), 1 vom: 07. Aug. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:21 year:2020 number:1 day:07 month:08 https://dx.doi.org/10.1186/s13059-020-02116-x kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.13 ASE 42.20 ASE AR 21 2020 1 07 08
allfieldsSound	10.1186/s13059-020-02116-x doi (DE-627)SPR040592529 (SPR)s13059-020-02116-x-e DE-627 ger DE-627 rakwb eng 570 ASE 42.13 bkl 42.20 bkl Wang, Chenfei verfasserin aut Integrative analyses of single-cell transcriptome and regulome using MAESTRO 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Single-cell RNA-seq (dpeaa)DE-He213 Single-cell ATAC-seq (dpeaa)DE-He213 Computational workflow (dpeaa)DE-He213 Integrate scRNA-seq and scATAC-seq (dpeaa)DE-He213 Cell-type annotation (dpeaa)DE-He213 Predict transcriptional regulators (dpeaa)DE-He213 Sun, Dongqing verfasserin aut Huang, Xin verfasserin aut Wan, Changxin verfasserin aut Li, Ziyi verfasserin aut Han, Ya verfasserin aut Qin, Qian verfasserin aut Fan, Jingyu verfasserin aut Qiu, Xintao verfasserin aut Xie, Yingtian verfasserin aut Meyer, Clifford A. verfasserin aut Brown, Myles verfasserin aut Tang, Ming verfasserin aut Long, Henry verfasserin aut Liu, Tao verfasserin aut Liu, X. Shirley verfasserin aut Enthalten in Genome biology London : BioMed Central, 2000 21(2020), 1 vom: 07. Aug. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:21 year:2020 number:1 day:07 month:08 https://dx.doi.org/10.1186/s13059-020-02116-x kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 42.13 ASE 42.20 ASE AR 21 2020 1 07 08
language	English
source	Enthalten in Genome biology 21(2020), 1 vom: 07. Aug. volume:21 year:2020 number:1 day:07 month:08
sourceStr	Enthalten in Genome biology 21(2020), 1 vom: 07. Aug. volume:21 year:2020 number:1 day:07 month:08
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Single-cell RNA-seq Single-cell ATAC-seq Computational workflow Integrate scRNA-seq and scATAC-seq Cell-type annotation Predict transcriptional regulators
dewey-raw	570
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container_title	Genome biology
authorswithroles_txt_mv	Wang, Chenfei @@aut@@ Sun, Dongqing @@aut@@ Huang, Xin @@aut@@ Wan, Changxin @@aut@@ Li, Ziyi @@aut@@ Han, Ya @@aut@@ Qin, Qian @@aut@@ Fan, Jingyu @@aut@@ Qiu, Xintao @@aut@@ Xie, Yingtian @@aut@@ Meyer, Clifford A. @@aut@@ Brown, Myles @@aut@@ Tang, Ming @@aut@@ Long, Henry @@aut@@ Liu, Tao @@aut@@ Liu, X. Shirley @@aut@@
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author	Wang, Chenfei
spellingShingle	Wang, Chenfei ddc 570 bkl 42.13 bkl 42.20 misc Single-cell RNA-seq misc Single-cell ATAC-seq misc Computational workflow misc Integrate scRNA-seq and scATAC-seq misc Cell-type annotation misc Predict transcriptional regulators Integrative analyses of single-cell transcriptome and regulome using MAESTRO
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topic_title	570 ASE 42.13 bkl 42.20 bkl Integrative analyses of single-cell transcriptome and regulome using MAESTRO Single-cell RNA-seq (dpeaa)DE-He213 Single-cell ATAC-seq (dpeaa)DE-He213 Computational workflow (dpeaa)DE-He213 Integrate scRNA-seq and scATAC-seq (dpeaa)DE-He213 Cell-type annotation (dpeaa)DE-He213 Predict transcriptional regulators (dpeaa)DE-He213
topic	ddc 570 bkl 42.13 bkl 42.20 misc Single-cell RNA-seq misc Single-cell ATAC-seq misc Computational workflow misc Integrate scRNA-seq and scATAC-seq misc Cell-type annotation misc Predict transcriptional regulators
topic_unstemmed	ddc 570 bkl 42.13 bkl 42.20 misc Single-cell RNA-seq misc Single-cell ATAC-seq misc Computational workflow misc Integrate scRNA-seq and scATAC-seq misc Cell-type annotation misc Predict transcriptional regulators
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title	Integrative analyses of single-cell transcriptome and regulome using MAESTRO
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title_full	Integrative analyses of single-cell transcriptome and regulome using MAESTRO
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author_browse	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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title_sort	integrative analyses of single-cell transcriptome and regulome using maestro
title_auth	Integrative analyses of single-cell transcriptome and regulome using MAESTRO
abstract	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.
abstractGer	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.
abstract_unstemmed	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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title_short	Integrative analyses of single-cell transcriptome and regulome using MAESTRO
url	https://dx.doi.org/10.1186/s13059-020-02116-x
remote_bool	true
author2	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
author2Str	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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doi_str	10.1186/s13059-020-02116-x
up_date	2024-07-03T16:59:31.083Z
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Integrative analyses of single-cell transcriptome and regulome using MAESTRO

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