Literature DB >> 33637727

Comprehensive analysis of single cell ATAC-seq data with SnapATAC.

Rongxin Fang1,2, Sebastian Preissl3, Yang Li1, Xiaomeng Hou3, Jacinta Lucero4, Xinxin Wang3, Amir Motamedi5, Andrew K Shiau5, Xinzhu Zhou6, Fangming Xie7, Eran A Mukamel7, Kai Zhang1, Yanxiao Zhang1, M Margarita Behrens4, Joseph R Ecker4,8, Bing Ren9,10,11.   

Abstract

Identification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by sample heterogeneity. Single cell analysis of accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volume of data pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC dissects cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nyström method, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC is applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis reveals ~370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate cell-type specific transcriptional regulators.

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Year:  2021        PMID: 33637727      PMCID: PMC7910485          DOI: 10.1038/s41467-021-21583-9

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  46 in total

Review 1.  Mechanisms and functional implications of adult neurogenesis.

Authors:  Chunmei Zhao; Wei Deng; Fred H Gage
Journal:  Cell       Date:  2008-02-22       Impact factor: 41.582

Review 2.  CTCF: master weaver of the genome.

Authors:  Jennifer E Phillips; Victor G Corces
Journal:  Cell       Date:  2009-06-26       Impact factor: 41.582

3.  Comprehensive Integration of Single-Cell Data.

Authors:  Tim Stuart; Andrew Butler; Paul Hoffman; Christoph Hafemeister; Efthymia Papalexi; William M Mauck; Yuhan Hao; Marlon Stoeckius; Peter Smibert; Rahul Satija
Journal:  Cell       Date:  2019-06-06       Impact factor: 41.582

4.  GREAT improves functional interpretation of cis-regulatory regions.

Authors:  Cory Y McLean; Dave Bristor; Michael Hiller; Shoa L Clarke; Bruce T Schaar; Craig B Lowe; Aaron M Wenger; Gill Bejerano
Journal:  Nat Biotechnol       Date:  2010-05-02       Impact factor: 54.908

5.  A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility.

Authors:  Darren A Cusanovich; Andrew J Hill; Delasa Aghamirzaie; Riza M Daza; Hannah A Pliner; Joel B Berletch; Galina N Filippova; Xingfan Huang; Lena Christiansen; William S DeWitt; Choli Lee; Samuel G Regalado; David F Read; Frank J Steemers; Christine M Disteche; Cole Trapnell; Jay Shendure
Journal:  Cell       Date:  2018-08-02       Impact factor: 41.582

Review 6.  The diversity of GABAergic neurons and neural communication elements.

Authors:  Z Josh Huang; Anirban Paul
Journal:  Nat Rev Neurosci       Date:  2019-06-20       Impact factor: 34.870

7.  The cis-regulatory dynamics of embryonic development at single-cell resolution.

Authors:  Darren A Cusanovich; James P Reddington; David A Garfield; Riza M Daza; Delasa Aghamirzaie; Raquel Marco-Ferreres; Hannah A Pliner; Lena Christiansen; Xiaojie Qiu; Frank J Steemers; Cole Trapnell; Jay Shendure; Eileen E M Furlong
Journal:  Nature       Date:  2018-03-14       Impact factor: 49.962

8.  High-throughput chromatin accessibility profiling at single-cell resolution.

Authors:  Anja Mezger; Sandy Klemm; Ishminder Mann; Kara Brower; Alain Mir; Magnolia Bostick; Andrew Farmer; Polly Fordyce; Sten Linnarsson; William Greenleaf
Journal:  Nat Commun       Date:  2018-09-07       Impact factor: 14.919

9.  Molecular Architecture of the Mouse Nervous System.

Authors:  Amit Zeisel; Hannah Hochgerner; Peter Lönnerberg; Anna Johnsson; Fatima Memic; Job van der Zwan; Martin Häring; Emelie Braun; Lars E Borm; Gioele La Manno; Simone Codeluppi; Alessandro Furlan; Kawai Lee; Nathan Skene; Kenneth D Harris; Jens Hjerling-Leffler; Ernest Arenas; Patrik Ernfors; Ulrika Marklund; Sten Linnarsson
Journal:  Cell       Date:  2018-08-09       Impact factor: 41.582

Review 10.  From reads to insight: a hitchhiker's guide to ATAC-seq data analysis.

Authors:  Feng Yan; David R Powell; David J Curtis; Nicholas C Wong
Journal:  Genome Biol       Date:  2020-02-03       Impact factor: 13.583

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  66 in total

1.  OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions.

Authors:  Shengquan Chen; Qiao Liu; Xuejian Cui; Zhanying Feng; Chunquan Li; Xiaowo Wang; Xuegong Zhang; Yong Wang; Rui Jiang
Journal:  Nucleic Acids Res       Date:  2021-07-02       Impact factor: 16.971

2.  A genetic map of the mouse dorsal vagal complex and its role in obesity.

Authors:  Mette Q Ludwig; Wenwen Cheng; Desiree Gordian; Julie Lee; Sarah J Paulsen; Stine N Hansen; Kristoffer L Egerod; Pernille Barkholt; Christopher J Rhodes; Anna Secher; Lotte Bjerre Knudsen; Charles Pyke; Martin G Myers; Tune H Pers
Journal:  Nat Metab       Date:  2021-03-25

3.  Single-Cell Transcriptomic and Epigenetic Analyses of Mouse Mammary Development Starting with the Embryo.

Authors:  Zhibo Ma; Nikki K Lytle; Cynthia Ramos; Razia F Naeem; Geoffrey M Wahl
Journal:  Methods Mol Biol       Date:  2022

4.  A single-cell atlas of chromatin accessibility in the human genome.

Authors:  Kai Zhang; James D Hocker; Michael Miller; Xiaomeng Hou; Joshua Chiou; Olivier B Poirion; Yunjiang Qiu; Yang E Li; Kyle J Gaulton; Allen Wang; Sebastian Preissl; Bing Ren
Journal:  Cell       Date:  2021-11-12       Impact factor: 41.582

5.  Single nucleus multi-omics identifies human cortical cell regulatory genome diversity.

Authors:  Chongyuan Luo; Hanqing Liu; Fangming Xie; Ethan J Armand; Kimberly Siletti; Trygve E Bakken; Rongxin Fang; Wayne I Doyle; Tim Stuart; Rebecca D Hodge; Lijuan Hu; Bang-An Wang; Zhuzhu Zhang; Sebastian Preissl; Dong-Sung Lee; Jingtian Zhou; Sheng-Yong Niu; Rosa Castanon; Anna Bartlett; Angeline Rivkin; Xinxin Wang; Jacinta Lucero; Joseph R Nery; David A Davis; Deborah C Mash; Rahul Satija; Jesse R Dixon; Sten Linnarsson; Ed Lein; M Margarita Behrens; Bing Ren; Eran A Mukamel; Joseph R Ecker
Journal:  Cell Genom       Date:  2022-03-09

6.  scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species.

Authors:  Tianshun Gao; Zilong Zheng; Yihang Pan; Chengming Zhu; Fuxin Wei; Jinqiu Yuan; Rui Sun; Shuo Fang; Nan Wang; Yang Zhou; Jiang Qian
Journal:  Nucleic Acids Res       Date:  2022-01-07       Impact factor: 16.971

7.  Simultaneous deep generative modeling and clustering of single cell genomic data.

Authors:  Qiao Liu; Shengquan Chen; Rui Jiang; Wing Hung Wong
Journal:  Nat Mach Intell       Date:  2021-05-10

8.  Functional enhancer elements drive subclass-selective expression from mouse to primate neocortex.

Authors:  John K Mich; Lucas T Graybuck; Erik E Hess; Joseph T Mahoney; Yoshiko Kojima; Yi Ding; Saroja Somasundaram; Jeremy A Miller; Brian E Kalmbach; Cristina Radaelli; Bryan B Gore; Natalie Weed; Victoria Omstead; Yemeserach Bishaw; Nadiya V Shapovalova; Refugio A Martinez; Olivia Fong; Shenqin Yao; Marty Mortrud; Peter Chong; Luke Loftus; Darren Bertagnolli; Jeff Goldy; Tamara Casper; Nick Dee; Ximena Opitz-Araya; Ali Cetin; Kimberly A Smith; Ryder P Gwinn; Charles Cobbs; Andrew L Ko; Jeffrey G Ojemann; C Dirk Keene; Daniel L Silbergeld; Susan M Sunkin; Viviana Gradinaru; Gregory D Horwitz; Hongkui Zeng; Bosiljka Tasic; Ed S Lein; Jonathan T Ting; Boaz P Levi
Journal:  Cell Rep       Date:  2021-03-30       Impact factor: 9.423

Review 9.  New horizons in the stormy sea of multimodal single-cell data integration.

Authors:  Christopher A Jackson; Christine Vogel
Journal:  Mol Cell       Date:  2022-01-20       Impact factor: 17.970

10.  SAILER: scalable and accurate invariant representation learning for single-cell ATAC-seq processing and integration.

Authors:  Yingxin Cao; Laiyi Fu; Jie Wu; Qinke Peng; Qing Nie; Jing Zhang; Xiaohui Xie
Journal:  Bioinformatics       Date:  2021-07-12       Impact factor: 6.937

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