High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of chromatin interactions and 3D chromosome folding on a larger scale. A graph-based multi-level representation of Hi-C data is essential for proper visualisation of the spatial pattern they represent, in particular for comparing different experiments or for re-mapping omics-data in a space-aware context. The size of the HiC data hampers the straightforward use of currently available graph visualisation tools and libraries. In this paper, we present the first version of NeoHiC, a user-friendly web application for the progressive graph visualisation of Hi-C data based on the use of the Neo4j graph database. The user could select the richness of the environment of the query gene by choosing among a large number of proximity and distance metrics.

NeoHiC: A web application for the analysis of Hi-C data

Marco Aldinucci;
2020-01-01

Abstract

High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of chromatin interactions and 3D chromosome folding on a larger scale. A graph-based multi-level representation of Hi-C data is essential for proper visualisation of the spatial pattern they represent, in particular for comparing different experiments or for re-mapping omics-data in a space-aware context. The size of the HiC data hampers the straightforward use of currently available graph visualisation tools and libraries. In this paper, we present the first version of NeoHiC, a user-friendly web application for the progressive graph visualisation of Hi-C data based on the use of the Neo4j graph database. The user could select the richness of the environment of the query gene by choosing among a large number of proximity and distance metrics.
2020
Inglese
contributo
2 - Congresso
16th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2019
ita
2019
Internazionale
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Esperti anonimi
Springer Science and Business Media Deutschland GmbH
Heidelberg
GERMANIA
12313
98
107
10
978-3-030-63060-7
978-3-030-63061-4
Graph database; Graph visualisation; Hi-C; Web application
REGNO UNITO DI GRAN BRETAGNA
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4
info:eu-repo/semantics/conferenceObject
04-CONTRIBUTO IN ATTI DI CONVEGNO::04A-Conference paper in volume
Daniele D'Agostino; Pietro Liò; Marco Aldinucci; Ivan Merelli
273
open
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1766001
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