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EPIXplorer: A web server for prediction, analysis and visualization of enhancer-promoter interactions
Long distance enhancers can physically interact with promoters to regulate gene expression through formation of enhancer-promoter (E-P) interactions. Identification of E-P interactions is also important for profound understanding of normal developmental and disease-associated risk variants. Although...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252822/ https://www.ncbi.nlm.nih.gov/pubmed/35639508 http://dx.doi.org/10.1093/nar/gkac397 |
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author | Tang, Li Zhong, Zhizhou Lin, Yisheng Yang, Yifei Wang, Jun Martin, James F Li, Min |
author_facet | Tang, Li Zhong, Zhizhou Lin, Yisheng Yang, Yifei Wang, Jun Martin, James F Li, Min |
author_sort | Tang, Li |
collection | PubMed |
description | Long distance enhancers can physically interact with promoters to regulate gene expression through formation of enhancer-promoter (E-P) interactions. Identification of E-P interactions is also important for profound understanding of normal developmental and disease-associated risk variants. Although the state-of-art predictive computation methods facilitate the identification of E-P interactions to a certain extent, currently there is no efficient method that can meet various requirements of usage. Here we developed EPIXplorer, a user-friendly web server for efficient prediction, analysis and visualization of E-P interactions. EPIXplorer integrates 9 robust predictive algorithms, supports multiple types of 3D contact data and multi-omics data as input. The output from EPIXplorer is scored, fully annotated by regulatory elements and risk single-nucleotide polymorphisms (SNPs). In addition, the Visualization and Downstream module provide further functional analysis, all the output files and high-quality images are available for download. Together, EPIXplorer provides a user-friendly interface to predict the E-P interactions in an acceptable time, as well as understand how the genome-wide association study (GWAS) variants influence disease pathology by altering DNA looping between enhancers and the target gene promoters. EPIXplorer is available at https://www.csuligroup.com/EPIXplorer. |
format | Online Article Text |
id | pubmed-9252822 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92528222022-07-05 EPIXplorer: A web server for prediction, analysis and visualization of enhancer-promoter interactions Tang, Li Zhong, Zhizhou Lin, Yisheng Yang, Yifei Wang, Jun Martin, James F Li, Min Nucleic Acids Res Web Server Issue Long distance enhancers can physically interact with promoters to regulate gene expression through formation of enhancer-promoter (E-P) interactions. Identification of E-P interactions is also important for profound understanding of normal developmental and disease-associated risk variants. Although the state-of-art predictive computation methods facilitate the identification of E-P interactions to a certain extent, currently there is no efficient method that can meet various requirements of usage. Here we developed EPIXplorer, a user-friendly web server for efficient prediction, analysis and visualization of E-P interactions. EPIXplorer integrates 9 robust predictive algorithms, supports multiple types of 3D contact data and multi-omics data as input. The output from EPIXplorer is scored, fully annotated by regulatory elements and risk single-nucleotide polymorphisms (SNPs). In addition, the Visualization and Downstream module provide further functional analysis, all the output files and high-quality images are available for download. Together, EPIXplorer provides a user-friendly interface to predict the E-P interactions in an acceptable time, as well as understand how the genome-wide association study (GWAS) variants influence disease pathology by altering DNA looping between enhancers and the target gene promoters. EPIXplorer is available at https://www.csuligroup.com/EPIXplorer. Oxford University Press 2022-05-25 /pmc/articles/PMC9252822/ /pubmed/35639508 http://dx.doi.org/10.1093/nar/gkac397 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. 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 | Web Server Issue Tang, Li Zhong, Zhizhou Lin, Yisheng Yang, Yifei Wang, Jun Martin, James F Li, Min EPIXplorer: A web server for prediction, analysis and visualization of enhancer-promoter interactions |
title | EPIXplorer: A web server for prediction, analysis and visualization of enhancer-promoter interactions |
title_full | EPIXplorer: A web server for prediction, analysis and visualization of enhancer-promoter interactions |
title_fullStr | EPIXplorer: A web server for prediction, analysis and visualization of enhancer-promoter interactions |
title_full_unstemmed | EPIXplorer: A web server for prediction, analysis and visualization of enhancer-promoter interactions |
title_short | EPIXplorer: A web server for prediction, analysis and visualization of enhancer-promoter interactions |
title_sort | epixplorer: a web server for prediction, analysis and visualization of enhancer-promoter interactions |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252822/ https://www.ncbi.nlm.nih.gov/pubmed/35639508 http://dx.doi.org/10.1093/nar/gkac397 |
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