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 / D'Agostino, D.; Lio, P.; Aldinucci, M.; Merelli, I.. - 12313:(2020), pp. 98-107. (Intervento presentato al convegno 16th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2019 tenutosi a Bergamo; ita) [10.1007/978-3-030-63061-4_10].
NeoHiC: A web application for the analysis of Hi-C data
Lio P.;
2020
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.File | Dimensione | Formato | |
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