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A Cosine Similarity-Based Method to Infer Variability of Chromatin Accessibility at the Single-Cell Level

Cellular identity between generations of developing cells is propagated through the epigenome particularly via the accessible parts of the chromatin. It is now possible to measure chromatin accessibility at single-cell resolution using single-cell assay for transposase accessible chromatin (scATAC-s...

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Autores principales: Cai, Stanley, Georgakilas, Georgios K., Johnson, John L., Vahedi, Golnaz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103536/
https://www.ncbi.nlm.nih.gov/pubmed/30158954
http://dx.doi.org/10.3389/fgene.2018.00319
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author Cai, Stanley
Georgakilas, Georgios K.
Johnson, John L.
Vahedi, Golnaz
author_facet Cai, Stanley
Georgakilas, Georgios K.
Johnson, John L.
Vahedi, Golnaz
author_sort Cai, Stanley
collection PubMed
description Cellular identity between generations of developing cells is propagated through the epigenome particularly via the accessible parts of the chromatin. It is now possible to measure chromatin accessibility at single-cell resolution using single-cell assay for transposase accessible chromatin (scATAC-seq), which can reveal the regulatory variation behind the phenotypic variation. However, single-cell chromatin accessibility data are sparse, binary, and high dimensional, leading to unique computational challenges. To overcome these difficulties, we developed PRISM, a computational workflow that quantifies cell-to-cell chromatin accessibility variation while controlling for technical biases. PRISM is a novel multidimensional scaling-based method using angular cosine distance metrics coupled with distance from the spatial centroid. PRISM takes differences in accessibility at each genomic region between single cells into account. Using data generated in our lab and publicly available, we showed that PRISM outperforms an existing algorithm, which relies on the aggregate of signal across a set of genomic regions. PRISM showed robustness to noise in cells with low coverage for measuring chromatin accessibility. Our approach revealed the previously undetected accessibility variation where accessible sites differ between cells but the total number of accessible sites is constant. We also showed that PRISM, but not an existing algorithm, can find suppressed heterogeneity of accessibility at CTCF binding sites. Our updated approach uncovers new biological results with profound implications on the cellular heterogeneity of chromatin architecture.
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spelling pubmed-61035362018-08-29 A Cosine Similarity-Based Method to Infer Variability of Chromatin Accessibility at the Single-Cell Level Cai, Stanley Georgakilas, Georgios K. Johnson, John L. Vahedi, Golnaz Front Genet Genetics Cellular identity between generations of developing cells is propagated through the epigenome particularly via the accessible parts of the chromatin. It is now possible to measure chromatin accessibility at single-cell resolution using single-cell assay for transposase accessible chromatin (scATAC-seq), which can reveal the regulatory variation behind the phenotypic variation. However, single-cell chromatin accessibility data are sparse, binary, and high dimensional, leading to unique computational challenges. To overcome these difficulties, we developed PRISM, a computational workflow that quantifies cell-to-cell chromatin accessibility variation while controlling for technical biases. PRISM is a novel multidimensional scaling-based method using angular cosine distance metrics coupled with distance from the spatial centroid. PRISM takes differences in accessibility at each genomic region between single cells into account. Using data generated in our lab and publicly available, we showed that PRISM outperforms an existing algorithm, which relies on the aggregate of signal across a set of genomic regions. PRISM showed robustness to noise in cells with low coverage for measuring chromatin accessibility. Our approach revealed the previously undetected accessibility variation where accessible sites differ between cells but the total number of accessible sites is constant. We also showed that PRISM, but not an existing algorithm, can find suppressed heterogeneity of accessibility at CTCF binding sites. Our updated approach uncovers new biological results with profound implications on the cellular heterogeneity of chromatin architecture. Frontiers Media S.A. 2018-08-15 /pmc/articles/PMC6103536/ /pubmed/30158954 http://dx.doi.org/10.3389/fgene.2018.00319 Text en Copyright © 2018 Cai, Georgakilas, Johnson and Vahedi. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Cai, Stanley
Georgakilas, Georgios K.
Johnson, John L.
Vahedi, Golnaz
A Cosine Similarity-Based Method to Infer Variability of Chromatin Accessibility at the Single-Cell Level
title A Cosine Similarity-Based Method to Infer Variability of Chromatin Accessibility at the Single-Cell Level
title_full A Cosine Similarity-Based Method to Infer Variability of Chromatin Accessibility at the Single-Cell Level
title_fullStr A Cosine Similarity-Based Method to Infer Variability of Chromatin Accessibility at the Single-Cell Level
title_full_unstemmed A Cosine Similarity-Based Method to Infer Variability of Chromatin Accessibility at the Single-Cell Level
title_short A Cosine Similarity-Based Method to Infer Variability of Chromatin Accessibility at the Single-Cell Level
title_sort cosine similarity-based method to infer variability of chromatin accessibility at the single-cell level
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103536/
https://www.ncbi.nlm.nih.gov/pubmed/30158954
http://dx.doi.org/10.3389/fgene.2018.00319
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