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snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis
SUMMARY: Genome-wide chromosome conformation capture (Hi-C) is a technique that allows the study of 3D genome organization. Despite being widely used, analysis of Hi-C data is technically challenging and involves several time-consuming steps that often require manual involvement making it error pron...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10307938/ https://www.ncbi.nlm.nih.gov/pubmed/37397353 http://dx.doi.org/10.1093/bioadv/vbad080 |
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author | Gregoricchio, Sebastian Zwart, Wilbert |
author_facet | Gregoricchio, Sebastian Zwart, Wilbert |
author_sort | Gregoricchio, Sebastian |
collection | PubMed |
description | SUMMARY: Genome-wide chromosome conformation capture (Hi-C) is a technique that allows the study of 3D genome organization. Despite being widely used, analysis of Hi-C data is technically challenging and involves several time-consuming steps that often require manual involvement making it error prone, potentially affecting data reproducibility. In order to facilitate and simplify these analyses we implemented snHiC, a snakemake-based pipeline that allows for the generation of contact matrices at multiple resolutions in one single run, aggregation of individual samples into user-specified groups, detection of domains, compartments, loops and stripes and performance of differential compartment and chromatin interaction analyses. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/sebastian-gregoricchio/snHiC. A yaml-formatted file (snHiC/workflow/envs/snHiC_conda_env_stable.yaml) is available to build a compatible conda environment. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online. |
format | Online Article Text |
id | pubmed-10307938 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-103079382023-06-30 snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis Gregoricchio, Sebastian Zwart, Wilbert Bioinform Adv Application Note SUMMARY: Genome-wide chromosome conformation capture (Hi-C) is a technique that allows the study of 3D genome organization. Despite being widely used, analysis of Hi-C data is technically challenging and involves several time-consuming steps that often require manual involvement making it error prone, potentially affecting data reproducibility. In order to facilitate and simplify these analyses we implemented snHiC, a snakemake-based pipeline that allows for the generation of contact matrices at multiple resolutions in one single run, aggregation of individual samples into user-specified groups, detection of domains, compartments, loops and stripes and performance of differential compartment and chromatin interaction analyses. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/sebastian-gregoricchio/snHiC. A yaml-formatted file (snHiC/workflow/envs/snHiC_conda_env_stable.yaml) is available to build a compatible conda environment. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online. Oxford University Press 2023-06-21 /pmc/articles/PMC10307938/ /pubmed/37397353 http://dx.doi.org/10.1093/bioadv/vbad080 Text en © The Author(s) 2023. 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 | Application Note Gregoricchio, Sebastian Zwart, Wilbert snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis |
title |
snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis |
title_full |
snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis |
title_fullStr |
snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis |
title_full_unstemmed |
snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis |
title_short |
snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis |
title_sort | snhic: a complete and simplified snakemake pipeline for grouped hi-c data analysis |
topic | Application Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10307938/ https://www.ncbi.nlm.nih.gov/pubmed/37397353 http://dx.doi.org/10.1093/bioadv/vbad080 |
work_keys_str_mv | AT gregoricchiosebastian snhicacompleteandsimplifiedsnakemakepipelineforgroupedhicdataanalysis AT zwartwilbert snhicacompleteandsimplifiedsnakemakepipelineforgroupedhicdataanalysis |