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HiCRep.py: fast comparison of Hi-C contact matrices in Python
MOTIVATION: Hi-C is the most widely used assay for investigating genome-wide 3D organization of chromatin. When working with Hi-C data, it is often useful to calculate the similarity between contact matrices in order to assess experimental reproducibility or to quantify relationships among Hi-C data...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479650/ https://www.ncbi.nlm.nih.gov/pubmed/33576390 http://dx.doi.org/10.1093/bioinformatics/btab097 |
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author | Lin, Dejun Sanders, Justin Noble, William Stafford |
author_facet | Lin, Dejun Sanders, Justin Noble, William Stafford |
author_sort | Lin, Dejun |
collection | PubMed |
description | MOTIVATION: Hi-C is the most widely used assay for investigating genome-wide 3D organization of chromatin. When working with Hi-C data, it is often useful to calculate the similarity between contact matrices in order to assess experimental reproducibility or to quantify relationships among Hi-C data from related samples. The HiCRep algorithm has been widely adopted for this task, but the existing R implementation suffers from run time limitations on high-resolution Hi-C data or on large single-cell Hi-C datasets. RESULTS: We introduce a Python implementation of HiCRep and demonstrate that it is much faster and consumes much less memory than the existing R implementation. Furthermore, we give examples of HiCRep’s ability to accurately distinguish replicates from non-replicates and to reveal cell type structure among collections of Hi-C data. AVAILABILITY AND IMPLEMENTATION: HiCRep.py and its documentation are available with a GPL license at https://github.com/Noble-Lab/hicrep. The software may be installed automatically using the pip package installer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8479650 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84796502021-09-30 HiCRep.py: fast comparison of Hi-C contact matrices in Python Lin, Dejun Sanders, Justin Noble, William Stafford Bioinformatics Applications Notes MOTIVATION: Hi-C is the most widely used assay for investigating genome-wide 3D organization of chromatin. When working with Hi-C data, it is often useful to calculate the similarity between contact matrices in order to assess experimental reproducibility or to quantify relationships among Hi-C data from related samples. The HiCRep algorithm has been widely adopted for this task, but the existing R implementation suffers from run time limitations on high-resolution Hi-C data or on large single-cell Hi-C datasets. RESULTS: We introduce a Python implementation of HiCRep and demonstrate that it is much faster and consumes much less memory than the existing R implementation. Furthermore, we give examples of HiCRep’s ability to accurately distinguish replicates from non-replicates and to reveal cell type structure among collections of Hi-C data. AVAILABILITY AND IMPLEMENTATION: HiCRep.py and its documentation are available with a GPL license at https://github.com/Noble-Lab/hicrep. The software may be installed automatically using the pip package installer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-02-12 /pmc/articles/PMC8479650/ /pubmed/33576390 http://dx.doi.org/10.1093/bioinformatics/btab097 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Lin, Dejun Sanders, Justin Noble, William Stafford HiCRep.py: fast comparison of Hi-C contact matrices in Python |
title | HiCRep.py: fast comparison of Hi-C contact matrices in Python |
title_full | HiCRep.py: fast comparison of Hi-C contact matrices in Python |
title_fullStr | HiCRep.py: fast comparison of Hi-C contact matrices in Python |
title_full_unstemmed | HiCRep.py: fast comparison of Hi-C contact matrices in Python |
title_short | HiCRep.py: fast comparison of Hi-C contact matrices in Python |
title_sort | hicrep.py: fast comparison of hi-c contact matrices in python |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479650/ https://www.ncbi.nlm.nih.gov/pubmed/33576390 http://dx.doi.org/10.1093/bioinformatics/btab097 |
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