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Serpentine: a flexible 2D binning method for differential Hi-C analysis
MOTIVATION: Hi-C contact maps reflect the relative contact frequencies between pairs of genomic loci, quantified through deep sequencing. Differential analyses of these maps enable downstream biological interpretations. However, the multi-fractal nature of the chromatin polymer inside the cellular e...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320618/ https://www.ncbi.nlm.nih.gov/pubmed/32311033 http://dx.doi.org/10.1093/bioinformatics/btaa249 |
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author | Baudry, Lyam Millot, Gaël A Thierry, Agnes Koszul, Romain Scolari, Vittore F |
author_facet | Baudry, Lyam Millot, Gaël A Thierry, Agnes Koszul, Romain Scolari, Vittore F |
author_sort | Baudry, Lyam |
collection | PubMed |
description | MOTIVATION: Hi-C contact maps reflect the relative contact frequencies between pairs of genomic loci, quantified through deep sequencing. Differential analyses of these maps enable downstream biological interpretations. However, the multi-fractal nature of the chromatin polymer inside the cellular envelope results in contact frequency values spanning several orders of magnitude: contacts between loci pairs separated by large genomic distances are much sparser than closer pairs. The same is true for poorly covered regions, such as repeated sequences. Both distant and poorly covered regions translate into low signal-to-noise ratios. There is no clear consensus to address this limitation. RESULTS: We present Serpentine, a fast, flexible procedure operating on raw data, which considers the contacts in each region of a contact map. Binning is performed only when necessary on noisy regions, preserving informative ones. This results in high-quality, low-noise contact maps that can be conveniently visualized for rigorous comparative analyses. AVAILABILITY AND IMPLEMENTATION: Serpentine is available on the PyPI repository and https://github.com/koszullab/serpentine; documentation and tutorials are provided at https://serpentine.readthedocs.io/en/latest/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-7320618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-73206182020-07-01 Serpentine: a flexible 2D binning method for differential Hi-C analysis Baudry, Lyam Millot, Gaël A Thierry, Agnes Koszul, Romain Scolari, Vittore F Bioinformatics Original Papers MOTIVATION: Hi-C contact maps reflect the relative contact frequencies between pairs of genomic loci, quantified through deep sequencing. Differential analyses of these maps enable downstream biological interpretations. However, the multi-fractal nature of the chromatin polymer inside the cellular envelope results in contact frequency values spanning several orders of magnitude: contacts between loci pairs separated by large genomic distances are much sparser than closer pairs. The same is true for poorly covered regions, such as repeated sequences. Both distant and poorly covered regions translate into low signal-to-noise ratios. There is no clear consensus to address this limitation. RESULTS: We present Serpentine, a fast, flexible procedure operating on raw data, which considers the contacts in each region of a contact map. Binning is performed only when necessary on noisy regions, preserving informative ones. This results in high-quality, low-noise contact maps that can be conveniently visualized for rigorous comparative analyses. AVAILABILITY AND IMPLEMENTATION: Serpentine is available on the PyPI repository and https://github.com/koszullab/serpentine; documentation and tutorials are provided at https://serpentine.readthedocs.io/en/latest/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-06-15 2020-04-20 /pmc/articles/PMC7320618/ /pubmed/32311033 http://dx.doi.org/10.1093/bioinformatics/btaa249 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Papers Baudry, Lyam Millot, Gaël A Thierry, Agnes Koszul, Romain Scolari, Vittore F Serpentine: a flexible 2D binning method for differential Hi-C analysis |
title | Serpentine: a flexible 2D binning method for differential Hi-C analysis |
title_full | Serpentine: a flexible 2D binning method for differential Hi-C analysis |
title_fullStr | Serpentine: a flexible 2D binning method for differential Hi-C analysis |
title_full_unstemmed | Serpentine: a flexible 2D binning method for differential Hi-C analysis |
title_short | Serpentine: a flexible 2D binning method for differential Hi-C analysis |
title_sort | serpentine: a flexible 2d binning method for differential hi-c analysis |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320618/ https://www.ncbi.nlm.nih.gov/pubmed/32311033 http://dx.doi.org/10.1093/bioinformatics/btaa249 |
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