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GrapHi-C: graph-based visualization of Hi-C datasets

OBJECTIVES: Hi-C is a proximity-based ligation reaction used to detect regions of the genome that are close in 3D space (or “interacting”). Typically, results from Hi-C experiments (contact maps) are visualized as heatmaps or Circos plots. While informative, these visualizations do not directly repr...

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Detalles Bibliográficos
Autores principales: MacKay, Kimberly, Kusalik, Anthony, Eskiw, Christopher H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6025839/
https://www.ncbi.nlm.nih.gov/pubmed/29958536
http://dx.doi.org/10.1186/s13104-018-3507-2
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author MacKay, Kimberly
Kusalik, Anthony
Eskiw, Christopher H.
author_facet MacKay, Kimberly
Kusalik, Anthony
Eskiw, Christopher H.
author_sort MacKay, Kimberly
collection PubMed
description OBJECTIVES: Hi-C is a proximity-based ligation reaction used to detect regions of the genome that are close in 3D space (or “interacting”). Typically, results from Hi-C experiments (contact maps) are visualized as heatmaps or Circos plots. While informative, these visualizations do not directly represent genomic structure and folding, making the interpretation of the underlying 3D genomic organization obscured. Our objective was to generate a graph-based contact map representation that leads to a more intuitive structural visualization. RESULTS: Normalized contact maps were converted into undirected graphs where each vertex represented a genomic region and each edge represented a detected (intra- and inter-chromosomal) or known (linear) interaction between two regions. Each edge was weighted by the inverse of the linear distance (Hi-C experimental resolution) or the interaction frequency from the contact map. Graphs were generated based on this representation scheme for contact maps from existing fission yeast datasets. Originally, these datasets were used to (1) identify specific principles influencing fission yeast genome organization and (2) uncover changes in fission yeast genome organization during the cell cycle. When compared to the equivalent heatmaps and/or Circos plots, the graph-based visualizations more intuitively depicted the changes in genome organization described in the original studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-018-3507-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-60258392018-07-09 GrapHi-C: graph-based visualization of Hi-C datasets MacKay, Kimberly Kusalik, Anthony Eskiw, Christopher H. BMC Res Notes Research Note OBJECTIVES: Hi-C is a proximity-based ligation reaction used to detect regions of the genome that are close in 3D space (or “interacting”). Typically, results from Hi-C experiments (contact maps) are visualized as heatmaps or Circos plots. While informative, these visualizations do not directly represent genomic structure and folding, making the interpretation of the underlying 3D genomic organization obscured. Our objective was to generate a graph-based contact map representation that leads to a more intuitive structural visualization. RESULTS: Normalized contact maps were converted into undirected graphs where each vertex represented a genomic region and each edge represented a detected (intra- and inter-chromosomal) or known (linear) interaction between two regions. Each edge was weighted by the inverse of the linear distance (Hi-C experimental resolution) or the interaction frequency from the contact map. Graphs were generated based on this representation scheme for contact maps from existing fission yeast datasets. Originally, these datasets were used to (1) identify specific principles influencing fission yeast genome organization and (2) uncover changes in fission yeast genome organization during the cell cycle. When compared to the equivalent heatmaps and/or Circos plots, the graph-based visualizations more intuitively depicted the changes in genome organization described in the original studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-018-3507-2) contains supplementary material, which is available to authorized users. BioMed Central 2018-06-29 /pmc/articles/PMC6025839/ /pubmed/29958536 http://dx.doi.org/10.1186/s13104-018-3507-2 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Note
MacKay, Kimberly
Kusalik, Anthony
Eskiw, Christopher H.
GrapHi-C: graph-based visualization of Hi-C datasets
title GrapHi-C: graph-based visualization of Hi-C datasets
title_full GrapHi-C: graph-based visualization of Hi-C datasets
title_fullStr GrapHi-C: graph-based visualization of Hi-C datasets
title_full_unstemmed GrapHi-C: graph-based visualization of Hi-C datasets
title_short GrapHi-C: graph-based visualization of Hi-C datasets
title_sort graphi-c: graph-based visualization of hi-c datasets
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6025839/
https://www.ncbi.nlm.nih.gov/pubmed/29958536
http://dx.doi.org/10.1186/s13104-018-3507-2
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