HiBrowse: multi-purpose statistical analysis of genome-wide chromatin 3D organization

doi:10.1093/bioinformatics/btu082

. 2014 Jun 1;30(11):1620-2.

doi: 10.1093/bioinformatics/btu082. Epub 2014 Feb 7.

HiBrowse: multi-purpose statistical analysis of genome-wide chromatin 3D organization

Jonas Paulsen¹, Geir Kjetil Sandve¹, Sveinung Gundersen¹, Tonje G Lien¹, Kai Trengereid¹, Eivind Hovig²

Affiliations

¹ Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Norway.
² Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, NorwayInstitute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, NorwayInstitute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Norway.

PMID: 24511080
PMCID: PMC4029040
DOI: 10.1093/bioinformatics/btu082

HiBrowse: multi-purpose statistical analysis of genome-wide chromatin 3D organization

Jonas Paulsen et al. Bioinformatics. 2014.

. 2014 Jun 1;30(11):1620-2.

doi: 10.1093/bioinformatics/btu082. Epub 2014 Feb 7.

Authors

Jonas Paulsen¹, Geir Kjetil Sandve¹, Sveinung Gundersen¹, Tonje G Lien¹, Kai Trengereid¹, Eivind Hovig²

Affiliations

¹ Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Norway.
² Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, NorwayInstitute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, NorwayInstitute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Norway.

PMID: 24511080
PMCID: PMC4029040
DOI: 10.1093/bioinformatics/btu082

Abstract

Recently developed methods that couple next-generation sequencing with chromosome conformation capture-based techniques, such as Hi-C and ChIA-PET, allow for characterization of genome-wide chromatin 3D structure. Understanding the organization of chromatin in three dimensions is a crucial next step in the unraveling of global gene regulation, and methods for analyzing such data are needed. We have developed HiBrowse, a user-friendly web-tool consisting of a range of hypothesis-based and descriptive statistics, using realistic assumptions in null-models.

Availability and implementation: HiBrowse is supported by all major browsers, and is freely available at http://hyperbrowser.uio.no/3d. Software is implemented in Python, and source code is available for download by following instructions on the main site.

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Figures

**Fig. 1.**
(A) Overview of statistical hypothesis tests implemented in HiBrowse. See Gundersen *et al.* (2011) for an in-depth explanation of track types, and the Supplementary Material for details about each statistic. (B) Example of a HiBrowse analysis using the ‘Linked elements more/less co-localized in 3D?’ statistic, investigating whether fusion transcripts are co-localized in 3D. (C) Result page from the analysis, presenting the question asked by the user together with both a simplistic and a more detailed answer giving the P-value and model assumption details. Links are provided to full details of the results at individual chromosome regions

See this image and copyright information in PMC

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References

1. Baù D, et al. The three-dimensional folding of the α-globin gene domain reveals formation of chromatin globules. Nat. Struct. Mol. Biol. 2010;18:107–114. - PMC - PubMed
1. Botta M, et al. Intra- and inter-chromosomal interactions correlate with CTCF binding genome wide. Mol. Syst. Biol. 2010;6 - PMC - PubMed
1. Fullwood MJ, et al. An oestrogen-receptor-α-bound human chromatin interactome. Nature. 2009;462:58–64. - PMC - PubMed
1. Goecks J, et al. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 2010;11:R86. - PMC - PubMed
1. Gundersen S, et al. Identifying elemental genomic track types and representing them uniformly. BMC Bioinformatics. 2011;12:494. - PMC - PubMed

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[1] Baù D, et al. The three-dimensional folding of the α-globin gene domain reveals formation of chromatin globules. Nat. Struct. Mol. Biol. 2010;18:107–114. - PMC - PubMed

[2] Baù D, et al. The three-dimensional folding of the α-globin gene domain reveals formation of chromatin globules. Nat. Struct. Mol. Biol. 2010;18:107–114. - PMC - PubMed

[3] Botta M, et al. Intra- and inter-chromosomal interactions correlate with CTCF binding genome wide. Mol. Syst. Biol. 2010;6 - PMC - PubMed

[4] Botta M, et al. Intra- and inter-chromosomal interactions correlate with CTCF binding genome wide. Mol. Syst. Biol. 2010;6 - PMC - PubMed

[5] Fullwood MJ, et al. An oestrogen-receptor-α-bound human chromatin interactome. Nature. 2009;462:58–64. - PMC - PubMed

[6] Fullwood MJ, et al. An oestrogen-receptor-α-bound human chromatin interactome. Nature. 2009;462:58–64. - PMC - PubMed

[7] Goecks J, et al. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 2010;11:R86. - PMC - PubMed

[8] Goecks J, et al. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 2010;11:R86. - PMC - PubMed

[9] Gundersen S, et al. Identifying elemental genomic track types and representing them uniformly. BMC Bioinformatics. 2011;12:494. - PMC - PubMed

[10] Gundersen S, et al. Identifying elemental genomic track types and representing them uniformly. BMC Bioinformatics. 2011;12:494. - PMC - PubMed

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HiBrowse: multi-purpose statistical analysis of genome-wide chromatin 3D organization

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HiBrowse: multi-purpose statistical analysis of genome-wide chromatin 3D organization

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