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dPeak: High Resolution Identification of Transcription Factor Binding Sites from PET and SET ChIP-Seq Data
Chromatin immunoprecipitation followed by high throughput sequencing (ChIP-Seq) has been successfully used for genome-wide profiling of transcription factor binding sites, histone modifications, and nucleosome occupancy in many model organisms and humans. Because the compact genomes of prokaryotes h...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3798280/ https://www.ncbi.nlm.nih.gov/pubmed/24146601 http://dx.doi.org/10.1371/journal.pcbi.1003246 |
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author | Chung, Dongjun Park, Dan Myers, Kevin Grass, Jeffrey Kiley, Patricia Landick, Robert Keleş, Sündüz |
author_facet | Chung, Dongjun Park, Dan Myers, Kevin Grass, Jeffrey Kiley, Patricia Landick, Robert Keleş, Sündüz |
author_sort | Chung, Dongjun |
collection | PubMed |
description | Chromatin immunoprecipitation followed by high throughput sequencing (ChIP-Seq) has been successfully used for genome-wide profiling of transcription factor binding sites, histone modifications, and nucleosome occupancy in many model organisms and humans. Because the compact genomes of prokaryotes harbor many binding sites separated by only few base pairs, applications of ChIP-Seq in this domain have not reached their full potential. Applications in prokaryotic genomes are further hampered by the fact that well studied data analysis methods for ChIP-Seq do not result in a resolution required for deciphering the locations of nearby binding events. We generated single-end tag (SET) and paired-end tag (PET) ChIP-Seq data for [Image: see text] factor in Escherichia coli (E. coli). Direct comparison of these datasets revealed that although PET assay enables higher resolution identification of binding events, standard ChIP-Seq analysis methods are not equipped to utilize PET-specific features of the data. To address this problem, we developed dPeak as a high resolution binding site identification (deconvolution) algorithm. dPeak implements a probabilistic model that accurately describes ChIP-Seq data generation process for both the SET and PET assays. For SET data, dPeak outperforms or performs comparably to the state-of-the-art high-resolution ChIP-Seq peak deconvolution algorithms such as PICS, GPS, and GEM. When coupled with PET data, dPeak significantly outperforms SET-based analysis with any of the current state-of-the-art methods. Experimental validations of a subset of dPeak predictions from [Image: see text] PET ChIP-Seq data indicate that dPeak can estimate locations of binding events with as high as [Image: see text] to [Image: see text] resolution. Applications of dPeak to [Image: see text] ChIP-Seq data in E. coli under aerobic and anaerobic conditions reveal closely located promoters that are differentially occupied and further illustrate the importance of high resolution analysis of ChIP-Seq data. |
format | Online Article Text |
id | pubmed-3798280 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37982802013-10-21 dPeak: High Resolution Identification of Transcription Factor Binding Sites from PET and SET ChIP-Seq Data Chung, Dongjun Park, Dan Myers, Kevin Grass, Jeffrey Kiley, Patricia Landick, Robert Keleş, Sündüz PLoS Comput Biol Research Article Chromatin immunoprecipitation followed by high throughput sequencing (ChIP-Seq) has been successfully used for genome-wide profiling of transcription factor binding sites, histone modifications, and nucleosome occupancy in many model organisms and humans. Because the compact genomes of prokaryotes harbor many binding sites separated by only few base pairs, applications of ChIP-Seq in this domain have not reached their full potential. Applications in prokaryotic genomes are further hampered by the fact that well studied data analysis methods for ChIP-Seq do not result in a resolution required for deciphering the locations of nearby binding events. We generated single-end tag (SET) and paired-end tag (PET) ChIP-Seq data for [Image: see text] factor in Escherichia coli (E. coli). Direct comparison of these datasets revealed that although PET assay enables higher resolution identification of binding events, standard ChIP-Seq analysis methods are not equipped to utilize PET-specific features of the data. To address this problem, we developed dPeak as a high resolution binding site identification (deconvolution) algorithm. dPeak implements a probabilistic model that accurately describes ChIP-Seq data generation process for both the SET and PET assays. For SET data, dPeak outperforms or performs comparably to the state-of-the-art high-resolution ChIP-Seq peak deconvolution algorithms such as PICS, GPS, and GEM. When coupled with PET data, dPeak significantly outperforms SET-based analysis with any of the current state-of-the-art methods. Experimental validations of a subset of dPeak predictions from [Image: see text] PET ChIP-Seq data indicate that dPeak can estimate locations of binding events with as high as [Image: see text] to [Image: see text] resolution. Applications of dPeak to [Image: see text] ChIP-Seq data in E. coli under aerobic and anaerobic conditions reveal closely located promoters that are differentially occupied and further illustrate the importance of high resolution analysis of ChIP-Seq data. Public Library of Science 2013-10-17 /pmc/articles/PMC3798280/ /pubmed/24146601 http://dx.doi.org/10.1371/journal.pcbi.1003246 Text en © 2013 Chung et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Chung, Dongjun Park, Dan Myers, Kevin Grass, Jeffrey Kiley, Patricia Landick, Robert Keleş, Sündüz dPeak: High Resolution Identification of Transcription Factor Binding Sites from PET and SET ChIP-Seq Data |
title | dPeak: High Resolution Identification of Transcription Factor Binding Sites from PET and SET ChIP-Seq Data |
title_full | dPeak: High Resolution Identification of Transcription Factor Binding Sites from PET and SET ChIP-Seq Data |
title_fullStr | dPeak: High Resolution Identification of Transcription Factor Binding Sites from PET and SET ChIP-Seq Data |
title_full_unstemmed | dPeak: High Resolution Identification of Transcription Factor Binding Sites from PET and SET ChIP-Seq Data |
title_short | dPeak: High Resolution Identification of Transcription Factor Binding Sites from PET and SET ChIP-Seq Data |
title_sort | dpeak: high resolution identification of transcription factor binding sites from pet and set chip-seq data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3798280/ https://www.ncbi.nlm.nih.gov/pubmed/24146601 http://dx.doi.org/10.1371/journal.pcbi.1003246 |
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