Cargando…
Comprehensive analysis of single cell ATAC-seq data with SnapATAC
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. Si...
Autores principales: | , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910485/ https://www.ncbi.nlm.nih.gov/pubmed/33637727 http://dx.doi.org/10.1038/s41467-021-21583-9 |
_version_ | 1783656127734480896 |
---|---|
author | 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 |
author_facet | 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 |
author_sort | Fang, Rongxin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7910485 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79104852021-03-04 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 Nat Commun Article 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. Nature Publishing Group UK 2021-02-26 /pmc/articles/PMC7910485/ /pubmed/33637727 http://dx.doi.org/10.1038/s41467-021-21583-9 Text en © The Author(s) 2021 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article 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 Comprehensive analysis of single cell ATAC-seq data with SnapATAC |
title | Comprehensive analysis of single cell ATAC-seq data with SnapATAC |
title_full | Comprehensive analysis of single cell ATAC-seq data with SnapATAC |
title_fullStr | Comprehensive analysis of single cell ATAC-seq data with SnapATAC |
title_full_unstemmed | Comprehensive analysis of single cell ATAC-seq data with SnapATAC |
title_short | Comprehensive analysis of single cell ATAC-seq data with SnapATAC |
title_sort | comprehensive analysis of single cell atac-seq data with snapatac |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910485/ https://www.ncbi.nlm.nih.gov/pubmed/33637727 http://dx.doi.org/10.1038/s41467-021-21583-9 |
work_keys_str_mv | AT fangrongxin comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT preisslsebastian comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT liyang comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT houxiaomeng comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT lucerojacinta comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT wangxinxin comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT motamediamir comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT shiauandrewk comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT zhouxinzhu comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT xiefangming comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT mukamelerana comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT zhangkai comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT zhangyanxiao comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT behrensmmargarita comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT eckerjosephr comprehensiveanalysisofsinglecellatacseqdatawithsnapatac AT renbing comprehensiveanalysisofsinglecellatacseqdatawithsnapatac |