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Benchmark of software tools for prokaryotic chromosomal interaction domain identification
MOTIVATION: The application of genome-wide chromosome conformation capture (3C) methods to prokaryotes provided insights into the spatial organization of their genomes and identified patterns conserved across the tree of life, such as chromatin compartments and contact domains. Prokaryotic genomes v...
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/PMC7653553/ https://www.ncbi.nlm.nih.gov/pubmed/32492116 http://dx.doi.org/10.1093/bioinformatics/btaa555 |
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author | Magnitov, Mikhail D Kuznetsova, Veronika S Ulianov, Sergey V Razin, Sergey V Tyakht, Alexander V |
author_facet | Magnitov, Mikhail D Kuznetsova, Veronika S Ulianov, Sergey V Razin, Sergey V Tyakht, Alexander V |
author_sort | Magnitov, Mikhail D |
collection | PubMed |
description | MOTIVATION: The application of genome-wide chromosome conformation capture (3C) methods to prokaryotes provided insights into the spatial organization of their genomes and identified patterns conserved across the tree of life, such as chromatin compartments and contact domains. Prokaryotic genomes vary in GC content and the density of restriction sites along the chromosome, suggesting that these properties should be considered when planning experiments and choosing appropriate software for data processing. Diverse algorithms are available for the analysis of eukaryotic chromatin contact maps, but their potential application to prokaryotic data has not yet been evaluated. RESULTS: Here, we present a comparative analysis of domain calling algorithms using available single-microbe experimental data. We evaluated the algorithms’ intra-dataset reproducibility, concordance with other tools and sensitivity to coverage and resolution of contact maps. Using RNA-seq as an example, we showed how orthogonal biological data can be utilized to validate the reliability and significance of annotated domains. We also suggest that in silico simulations of contact maps can be used to choose optimal restriction enzymes and estimate theoretical map resolutions before the experiment. Our results provide guidelines for researchers investigating microbes and microbial communities using high-throughput 3C assays such as Hi-C and 3C-seq. AVAILABILITY AND IMPLEMENTATION: The code of the analysis is available at https://github.com/magnitov/prokaryotic_cids. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-7653553 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-76535532020-11-16 Benchmark of software tools for prokaryotic chromosomal interaction domain identification Magnitov, Mikhail D Kuznetsova, Veronika S Ulianov, Sergey V Razin, Sergey V Tyakht, Alexander V Bioinformatics Original Papers MOTIVATION: The application of genome-wide chromosome conformation capture (3C) methods to prokaryotes provided insights into the spatial organization of their genomes and identified patterns conserved across the tree of life, such as chromatin compartments and contact domains. Prokaryotic genomes vary in GC content and the density of restriction sites along the chromosome, suggesting that these properties should be considered when planning experiments and choosing appropriate software for data processing. Diverse algorithms are available for the analysis of eukaryotic chromatin contact maps, but their potential application to prokaryotic data has not yet been evaluated. RESULTS: Here, we present a comparative analysis of domain calling algorithms using available single-microbe experimental data. We evaluated the algorithms’ intra-dataset reproducibility, concordance with other tools and sensitivity to coverage and resolution of contact maps. Using RNA-seq as an example, we showed how orthogonal biological data can be utilized to validate the reliability and significance of annotated domains. We also suggest that in silico simulations of contact maps can be used to choose optimal restriction enzymes and estimate theoretical map resolutions before the experiment. Our results provide guidelines for researchers investigating microbes and microbial communities using high-throughput 3C assays such as Hi-C and 3C-seq. AVAILABILITY AND IMPLEMENTATION: The code of the analysis is available at https://github.com/magnitov/prokaryotic_cids. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-08-27 /pmc/articles/PMC7653553/ /pubmed/32492116 http://dx.doi.org/10.1093/bioinformatics/btaa555 Text en © The Author(s) 2020. 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 (http://creativecommons.org/licenses/by/4.0/ (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 | Original Papers Magnitov, Mikhail D Kuznetsova, Veronika S Ulianov, Sergey V Razin, Sergey V Tyakht, Alexander V Benchmark of software tools for prokaryotic chromosomal interaction domain identification |
title | Benchmark of software tools for prokaryotic chromosomal interaction domain identification |
title_full | Benchmark of software tools for prokaryotic chromosomal interaction domain identification |
title_fullStr | Benchmark of software tools for prokaryotic chromosomal interaction domain identification |
title_full_unstemmed | Benchmark of software tools for prokaryotic chromosomal interaction domain identification |
title_short | Benchmark of software tools for prokaryotic chromosomal interaction domain identification |
title_sort | benchmark of software tools for prokaryotic chromosomal interaction domain identification |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653553/ https://www.ncbi.nlm.nih.gov/pubmed/32492116 http://dx.doi.org/10.1093/bioinformatics/btaa555 |
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