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Comprehensive analysis of single cell ATAC-seq data with SnapATAC.
Fang, Rongxin; Preissl, Sebastian; Li, Yang; Hou, Xiaomeng; Lucero, Jacinta; Wang, Xinxin; Motamedi, Amir; Shiau, Andrew K; Zhou, Xinzhu; Xie, Fangming; Mukamel, Eran A; Zhang, Kai; Zhang, Yanxiao; Behrens, M Margarita; Ecker, Joseph R; Ren, Bing.
Afiliação
  • Fang R; Ludwig Institute for Cancer Research, La Jolla, CA, USA.
  • Preissl S; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
  • Li Y; Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA.
  • Hou X; Ludwig Institute for Cancer Research, La Jolla, CA, USA.
  • Lucero J; Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA.
  • Wang X; The Salk Institute for Biological Studies, La Jolla, CA, USA.
  • Motamedi A; Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA.
  • Shiau AK; Small Molecule Discovery Program, Ludwig Institute for Cancer Research, La Jolla, CA, USA.
  • Zhou X; Small Molecule Discovery Program, Ludwig Institute for Cancer Research, La Jolla, CA, USA.
  • Xie F; Biomedical Science Graduate Program, University of California San Diego, La Jolla, CA, USA.
  • Mukamel EA; Department of Physics, University of California, San Diego, La Jolla, CA, USA.
  • Zhang K; Department of Physics, University of California, San Diego, La Jolla, CA, USA.
  • Zhang Y; Ludwig Institute for Cancer Research, La Jolla, CA, USA.
  • Behrens MM; Ludwig Institute for Cancer Research, La Jolla, CA, USA.
  • Ecker JR; The Salk Institute for Biological Studies, La Jolla, CA, USA.
  • Ren B; The Salk Institute for Biological Studies, La Jolla, CA, USA.
Nat Commun ; 12(1): 1337, 2021 02 26.
Article em En | MEDLINE | ID: mdl-33637727
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise de Célula Única / Sequenciamento de Cromatina por Imunoprecipitação Limite: Animals Idioma: En Revista: Nat Commun Assunto da revista: BIOLOGIA / CIENCIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise de Célula Única / Sequenciamento de Cromatina por Imunoprecipitação Limite: Animals Idioma: En Revista: Nat Commun Assunto da revista: BIOLOGIA / CIENCIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos