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Destin: toolkit for single-cell analysis of chromatin accessibility
SUMMARY: Single-cell assay of transposase-accessible chromatin followed by sequencing (scATAC-seq) is an emerging new technology for the study of gene regulation with single-cell resolution. The data from scATAC-seq are unique—sparse, binary and highly variable even within the same cell type. As suc...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761983/ https://www.ncbi.nlm.nih.gov/pubmed/30821321 http://dx.doi.org/10.1093/bioinformatics/btz141 |
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author | Urrutia, Eugene Chen, Li Zhou, Haibo Jiang, Yuchao |
author_facet | Urrutia, Eugene Chen, Li Zhou, Haibo Jiang, Yuchao |
author_sort | Urrutia, Eugene |
collection | PubMed |
description | SUMMARY: Single-cell assay of transposase-accessible chromatin followed by sequencing (scATAC-seq) is an emerging new technology for the study of gene regulation with single-cell resolution. The data from scATAC-seq are unique—sparse, binary and highly variable even within the same cell type. As such, neither methods developed for bulk ATAC-seq nor single-cell RNA-seq data are appropriate. Here, we present Destin, a bioinformatic and statistical framework for comprehensive scATAC-seq data analysis. Destin performs cell-type clustering via weighted principle component analysis, weighting accessible chromatin regions by existing genomic annotations and publicly available regulomic datasets. The weights and additional tuning parameters are determined via model-based likelihood. We evaluated the performance of Destin using downsampled bulk ATAC-seq data of purified samples and scATAC-seq data from seven diverse experiments. Compared to existing methods, Destin was shown to outperform across all datasets and platforms. For demonstration, we further applied Destin to 2088 adult mouse forebrain cells and identified cell-type-specific association of previously reported schizophrenia GWAS loci. AVAILABILITY AND IMPLEMENTATION: Destin toolkit is freely available as an R package at https://github.com/urrutiag/destin. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-6761983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-67619832019-10-02 Destin: toolkit for single-cell analysis of chromatin accessibility Urrutia, Eugene Chen, Li Zhou, Haibo Jiang, Yuchao Bioinformatics Applications Notes SUMMARY: Single-cell assay of transposase-accessible chromatin followed by sequencing (scATAC-seq) is an emerging new technology for the study of gene regulation with single-cell resolution. The data from scATAC-seq are unique—sparse, binary and highly variable even within the same cell type. As such, neither methods developed for bulk ATAC-seq nor single-cell RNA-seq data are appropriate. Here, we present Destin, a bioinformatic and statistical framework for comprehensive scATAC-seq data analysis. Destin performs cell-type clustering via weighted principle component analysis, weighting accessible chromatin regions by existing genomic annotations and publicly available regulomic datasets. The weights and additional tuning parameters are determined via model-based likelihood. We evaluated the performance of Destin using downsampled bulk ATAC-seq data of purified samples and scATAC-seq data from seven diverse experiments. Compared to existing methods, Destin was shown to outperform across all datasets and platforms. For demonstration, we further applied Destin to 2088 adult mouse forebrain cells and identified cell-type-specific association of previously reported schizophrenia GWAS loci. AVAILABILITY AND IMPLEMENTATION: Destin toolkit is freely available as an R package at https://github.com/urrutiag/destin. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-10-01 2019-03-01 /pmc/articles/PMC6761983/ /pubmed/30821321 http://dx.doi.org/10.1093/bioinformatics/btz141 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Urrutia, Eugene Chen, Li Zhou, Haibo Jiang, Yuchao Destin: toolkit for single-cell analysis of chromatin accessibility |
title | Destin: toolkit for single-cell analysis of chromatin accessibility |
title_full | Destin: toolkit for single-cell analysis of chromatin accessibility |
title_fullStr | Destin: toolkit for single-cell analysis of chromatin accessibility |
title_full_unstemmed | Destin: toolkit for single-cell analysis of chromatin accessibility |
title_short | Destin: toolkit for single-cell analysis of chromatin accessibility |
title_sort | destin: toolkit for single-cell analysis of chromatin accessibility |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761983/ https://www.ncbi.nlm.nih.gov/pubmed/30821321 http://dx.doi.org/10.1093/bioinformatics/btz141 |
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