Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data

Shounak Chakraborty; Stefan Canzar; Tobias Marschall; Marcel H. Schulz

doi:10.1007/978-3-319-89929-9_2

Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data

Shounak Chakraborty
, Stefan Canzar
, Tobias Marschall
, Marcel H. Schulz

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Measuring nucleosome positioning in cells is crucial for the analysis of epigenetic gene regulation. Reconstruction of nucleosome profiles of individual cells or subpopulations of cells remains challenging because most genome-wide assays measure nucleosome positioning and DNA accessibility for thousands of cells using bulk sequencing. Here we use characteristics of the NOMe-sequencing assay to derive a new approach, called ChromaClique, for deconvolution of different nucleosome profiles (chromatypes) from cell subpopulations of one NOMe-seq measurement. ChromaClique uses a maximal clique enumeration algorithm on a newly defined NOMe read graph that is able to group reads according to their nucleosome profiles. We show that the edge probabilities of that graph can be efficiently computed using Hidden Markov Models. We demonstrate using simulated data that ChromaClique is more accurate than a related method and scales favorably, allowing genome-wide analyses of chromatypes in cell subpopulations. Software is available at https://github.com/shounak1990/ChromaClique under MIT license.

Original language	English (US)
Title of host publication	Research in Computational Molecular Biology - 22nd Annual International Conference, RECOMB 2018, Proceedings
Editors	Benjamin J. Raphael
Publisher	Springer Verlag
Pages	21-36
Number of pages	16
ISBN (Print)	9783319899282
DOIs	https://doi.org/10.1007/978-3-319-89929-9_2
State	Published - 2018
Event	22nd International Conference on Research in Computational Molecular Biology, RECOMB 2018 - Paris, France Duration: Apr 21 2018 → Apr 24 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10812 LNBI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	22nd International Conference on Research in Computational Molecular Biology, RECOMB 2018
Country/Territory	France
City	Paris
Period	4/21/18 → 4/24/18

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-89929-9_2

Cite this

Chakraborty, S., Canzar, S., Marschall, T., & Schulz, M. H. (2018). Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data. In B. J. Raphael (Ed.), Research in Computational Molecular Biology - 22nd Annual International Conference, RECOMB 2018, Proceedings (pp. 21-36). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10812 LNBI). Springer Verlag. https://doi.org/10.1007/978-3-319-89929-9_2

Chakraborty, Shounak ; Canzar, Stefan ; Marschall, Tobias et al. / Chromatyping : Reconstructing Nucleosome Profiles from NOMe Sequencing Data. Research in Computational Molecular Biology - 22nd Annual International Conference, RECOMB 2018, Proceedings. editor / Benjamin J. Raphael. Springer Verlag, 2018. pp. 21-36 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{6511acc6ba3f459aa523b01689316a12,

title = "Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data",

abstract = "Measuring nucleosome positioning in cells is crucial for the analysis of epigenetic gene regulation. Reconstruction of nucleosome profiles of individual cells or subpopulations of cells remains challenging because most genome-wide assays measure nucleosome positioning and DNA accessibility for thousands of cells using bulk sequencing. Here we use characteristics of the NOMe-sequencing assay to derive a new approach, called ChromaClique, for deconvolution of different nucleosome profiles (chromatypes) from cell subpopulations of one NOMe-seq measurement. ChromaClique uses a maximal clique enumeration algorithm on a newly defined NOMe read graph that is able to group reads according to their nucleosome profiles. We show that the edge probabilities of that graph can be efficiently computed using Hidden Markov Models. We demonstrate using simulated data that ChromaClique is more accurate than a related method and scales favorably, allowing genome-wide analyses of chromatypes in cell subpopulations. Software is available at https://github.com/shounak1990/ChromaClique under MIT license.",

author = "Shounak Chakraborty and Stefan Canzar and Tobias Marschall and Schulz, \{Marcel H.\}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 22nd International Conference on Research in Computational Molecular Biology, RECOMB 2018 ; Conference date: 21-04-2018 Through 24-04-2018",

year = "2018",

doi = "10.1007/978-3-319-89929-9\_2",

language = "English (US)",

isbn = "9783319899282",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

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booktitle = "Research in Computational Molecular Biology - 22nd Annual International Conference, RECOMB 2018, Proceedings",

address = "Germany",

}

Chakraborty, S, Canzar, S, Marschall, T & Schulz, MH 2018, Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data. in BJ Raphael (ed.), Research in Computational Molecular Biology - 22nd Annual International Conference, RECOMB 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10812 LNBI, Springer Verlag, pp. 21-36, 22nd International Conference on Research in Computational Molecular Biology, RECOMB 2018, Paris, France, 4/21/18. https://doi.org/10.1007/978-3-319-89929-9_2

Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data. / Chakraborty, Shounak; Canzar, Stefan; Marschall, Tobias et al.
Research in Computational Molecular Biology - 22nd Annual International Conference, RECOMB 2018, Proceedings. ed. / Benjamin J. Raphael. Springer Verlag, 2018. p. 21-36 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10812 LNBI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Chromatyping

T2 - 22nd International Conference on Research in Computational Molecular Biology, RECOMB 2018

AU - Chakraborty, Shounak

AU - Canzar, Stefan

AU - Marschall, Tobias

AU - Schulz, Marcel H.

PY - 2018

Y1 - 2018

N2 - Measuring nucleosome positioning in cells is crucial for the analysis of epigenetic gene regulation. Reconstruction of nucleosome profiles of individual cells or subpopulations of cells remains challenging because most genome-wide assays measure nucleosome positioning and DNA accessibility for thousands of cells using bulk sequencing. Here we use characteristics of the NOMe-sequencing assay to derive a new approach, called ChromaClique, for deconvolution of different nucleosome profiles (chromatypes) from cell subpopulations of one NOMe-seq measurement. ChromaClique uses a maximal clique enumeration algorithm on a newly defined NOMe read graph that is able to group reads according to their nucleosome profiles. We show that the edge probabilities of that graph can be efficiently computed using Hidden Markov Models. We demonstrate using simulated data that ChromaClique is more accurate than a related method and scales favorably, allowing genome-wide analyses of chromatypes in cell subpopulations. Software is available at https://github.com/shounak1990/ChromaClique under MIT license.

AB - Measuring nucleosome positioning in cells is crucial for the analysis of epigenetic gene regulation. Reconstruction of nucleosome profiles of individual cells or subpopulations of cells remains challenging because most genome-wide assays measure nucleosome positioning and DNA accessibility for thousands of cells using bulk sequencing. Here we use characteristics of the NOMe-sequencing assay to derive a new approach, called ChromaClique, for deconvolution of different nucleosome profiles (chromatypes) from cell subpopulations of one NOMe-seq measurement. ChromaClique uses a maximal clique enumeration algorithm on a newly defined NOMe read graph that is able to group reads according to their nucleosome profiles. We show that the edge probabilities of that graph can be efficiently computed using Hidden Markov Models. We demonstrate using simulated data that ChromaClique is more accurate than a related method and scales favorably, allowing genome-wide analyses of chromatypes in cell subpopulations. Software is available at https://github.com/shounak1990/ChromaClique under MIT license.

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U2 - 10.1007/978-3-319-89929-9_2

DO - 10.1007/978-3-319-89929-9_2

M3 - Conference contribution

AN - SCOPUS:85046143242

SN - 9783319899282

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 36

BT - Research in Computational Molecular Biology - 22nd Annual International Conference, RECOMB 2018, Proceedings

A2 - Raphael, Benjamin J.

PB - Springer Verlag

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ER -

Chakraborty S, Canzar S, Marschall T, Schulz MH. Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data. In Raphael BJ, editor, Research in Computational Molecular Biology - 22nd Annual International Conference, RECOMB 2018, Proceedings. Springer Verlag. 2018. p. 21-36. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-89929-9_2

Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data

Abstract

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