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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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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. |
format | Online Article Text |
id | pubmed-6025839 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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