Graph-based Characterisations of Cell Types and Functionally Related Modules in Promoter Capture Hi-C Data

Lelde Lace; Gatis Melkus; Peteris Rucevskis; Edgars Celms; Karlis Cerans; Paulis Kikusts; Mārtiņš Opmanis; Darta Rituma; Juris Viksna

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Paper

Graph-based Characterisations of Cell Types and Functionally Related Modules in Promoter Capture Hi-C Data

Topics: Data Mining and Machine Learning; Genomics and Proteomics; Next Generation Sequencing; Pattern Recognition, Clustering and Classification; Structural Bioinformatics; Visualization

In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSTEC, 78-89, 2019 , Prague, Czech Republic

Authors: Lelde Lace ; Gatis Melkus ; Peteris Rucevskis ; Edgars Celms ; Karlis Cerans ; Paulis Kikusts ; Mārtiņš Opmanis ; Darta Rituma and Juris Viksna

Affiliation: Institute of Mathematics and Computer Science, University of Latvia, Rainis Boulevard 29, Riga, Latvia

Keyword(s): Hi-C Networks, Cell Type Specificity, Graph-Based Metrics, Graph Topology.

Abstract: Current technologies, noteworthy Hi-C, for chromosome conformation capture allow to understand a broad spectrum of functional interactions between genome elements. Although significant progress has been made, there are still a lot of open questions regarding best approaches for analysis of Hi-C data to identify biologically significant features. In this paper we approach this problem by focusing strictly on the topological properties of Hi-C interaction graphs. Graph topological properties were analysed from the perspective of two research questions: 1) are topological properties alone able to distinguish between different cell types and assign biologically meaningful distances between them; 2) what is a typical structure of Hi-C interaction graphs and can we assign a biological significance to structural elements or features? The analysis was applied to a set of Hi-C interactions in 17 human haematopoietic cell types. Promising results have been obtained at answering both questions. Firstly, we propose a concrete set Base11 of 11 topology-based metrics that provide good discriminatory power between cell types. Secondly, we have explored the topological features of connected components of Hi-C interaction graphs and demonstrate that such components tend to be well conserved within particular cell type subgroups and can be well associated with known biological processes. (More)

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Paper citation in several formats:

Lace, L.; Melkus, G.; Rucevskis, P.; Celms, E.; Cerans, K.; Kikusts, P.; Opmanis, M.; Rituma, D. and Viksna, J. (2019). Graph-based Characterisations of Cell Types and Functionally Related Modules in Promoter Capture Hi-C Data. In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOINFORMATICS; ISBN 978-989-758-353-7; ISSN 2184-4305, SciTePress, pages 78-89. DOI: 10.5220/0007390800780089

@conference{bioinformatics19,
author={Lelde Lace. and Gatis Melkus. and Peteris Rucevskis. and Edgars Celms. and Karlis Cerans. and Paulis Kikusts. and Mārtiņš Opmanis. and Darta Rituma. and Juris Viksna.},
title={Graph-based Characterisations of Cell Types and Functionally Related Modules in Promoter Capture Hi-C Data},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOINFORMATICS},
year={2019},
pages={78-89},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007390800780089},
isbn={978-989-758-353-7},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOINFORMATICS
TI - Graph-based Characterisations of Cell Types and Functionally Related Modules in Promoter Capture Hi-C Data
SN - 978-989-758-353-7
IS - 2184-4305
AU - Lace, L.
AU - Melkus, G.
AU - Rucevskis, P.
AU - Celms, E.
AU - Cerans, K.
AU - Kikusts, P.
AU - Opmanis, M.
AU - Rituma, D.
AU - Viksna, J.
PY - 2019
SP - 78
EP - 89
DO - 10.5220/0007390800780089
PB - SciTePress